•

The use, abllndance and conservation of woody species in the Batemi Valley, northwestern Tanzania

by Wynet Smith Department of Geography McGiII University Montreal, QC July 1993

A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfilment for the degree of Masters of Science • Cl Wynet Smith 1993 The use and conservation of woody species in nùrthwestern Tanzania Abstract

• Tbe Baten"i

TanzanIo l'l, ,", ,up lives a traditional suhsistence lifesty\e and arc thcrcforc

dependcnt l... ~ l' \ ~ccs th:'t :mrround t hem. This stuùy: 1) lI1Vt'stigatcs their lise

of woody \'cget. 't;(jn; _ \ :;îudies l~e abundance and dlstl ibutioll of woody vegetation

in the nrea; und ~)' rxr','riments \\>Ith assigllin,J use valucs to spccil~s ami \Vith

employing the~e ur, i,.,,' ~o identity c,JnservatlDll prioritlcs. The Batcmi utilize

over 100 -w01' l' '"'t ..., hmilies' and 58 gcne. a, from the environment

• surroundinf Lh' , \': 1 1, . 'I1struction, fuel, implements, services, food and

medicine. Ra,!,--,_"'. " systematic inventories in the valley showed that the

most abundant ~pfcies i "Ion dictygamous anù Acacia 1001iiis. Land cover in the

area can be classed in\o three mnin vegetation types llsing a polythetic divisive

program, TWINSPAN and these types are linkeù to three habitat types: hillsidc, plain

and riverine. A landcover map for the area was produceù l'rom Landsat TM digital

data. Based on density of woody vegetation. four categOI ies were chosen for the final

map product: thicket, woodland, wooded grassland, and grassland. To establish

conservation priorities, use values are assigned based on importance 01 a lise, number

of species that can fulfil tnat lise, and the rate of consumption. These values, whcn

compared to abundance, provide a framework for considering conservation priori tics.

Based on various methods, Acacia mellifera and HaplocoellllnJolioosum are identified

as two species that may require special attention .

• Resume

• Les Batemi ~ont un groupe agropastoral habitant une région semi-aride du nord-ouest de la Tanzanie. Le groupe vit de subsistences traditionnelles donc est dépendarl~ d~:) ressources naturelles environnantes. Cette étude 1) enquête sur l'usage qu'ils font de la végétation bOIsée 2) examine l'abondance et la distribution de la végétation boisée de la région 3) expérimente en classIfiant les espèces par une échelle de valeur-utilisation et utilisant cette échelle pour identl fier les priorités de conservation. Les Batemi utilisent au-dessus de 100 espèces forestières, dans 37 familles et 58 genera, trouvées dans la région environnante de leur village, pour des fins de constructions, combLlstion, outils, services, nourriture et médicine. Un échantillion choisie au hasard et un inventaire systématique dans la vallée démontrent que l'espèce la plus abondante est le Croton dictYMllmous et l'Acacia umilis. La couverture terrestre dans la région peut être classé en trois types de végétations principales selon le programme divisible polythetique le TWINSPAN et ces types sont reliés aux trois types d'habitat: fallaise, plaine et riverain. Une carte de la couverture terrestre de la région fut produite par Landsat TM digital data. Basé sur la densité des boisés, quatre catégories ont été choisies pour la production de la carte finale: bosquet, pays bOISé, savanne boisée et savanne. Afin d'établir les priorités de conservation, les espèces furent classées selon une échelle de valeur­ utilisation, basée sur l'importance de son utilisation, le nombre d'espèce qui répondent à cette utilisation et le taux. de consommation. Ces valeurs, une fois comparées à son abondance, procurent la base de travail dans la considération des priorités de conservation. Basé sur des méthodes variées, l'Acacia mellifera et Haploceolum folioosum sont deux espèces qui pourraient demander une attention spéciale .

• 11 Aclmowledgements

• There are a number of people that 1 must thank for thclr support and encouragement or hospitality. 1 will go by contment.

There are a number of people at McGill 1 would like to acknowlcdgc. Sp~cial

thanks to my supervisor, Thomas Meredith for hls encouragement, gUIdance, support,

and occasionally misplaced faith in me. Professors Theo Hil1s and TI \11 Johns, the othL'[

members of my committee, were also invaluable ~ourccs of lIlfOnnatlO1l and encouragement and provided useful feedback on the thcsls.

Lillian Lee of the GIS lab was incredib!j hcipful and patIent. Profc,,~or (lat! Chmura kindly allowed me to use her Mac computer to run a few programs. Professors Sherry OIson and Tim Moore provided hclpful cntical commento; on the last dralt.

1 would like to acknowledge ail the graduate and undergraduate ~tlldent~ whol11

provided fun and excitement alcng the way. A special thanks 10 Scot, E!J~a, Jcnlllfcr,

and Paul for st:mulating semmar convcr~ations. Thanks to Bruce and Jt!1 for CANOeO

and TWINSPAN lessons and advice. A very special thanks to Karen Richardson for the

use of her livingroom library, many dinner'i and more rccently, a place to ~tay.

My family i5 also thanked for putting up with me aIl thcsc ycar'i. 1 know yOll

sometimes worry about what l'm doing, ~o now you can sec 1 have :wtually donc something in the Jast year and a half.

The African contmgent is long. Tim Johns, Tom Kllnanil1l, and E. BOlllface

Mohoro are thanked for making my first two weeks in Batemi an cntertainlllg and

learning experience. Those dinner conversations wi Il be remcrnbcrcd for a long t!lne

with warmth and laughter. Tom also provided wondcrful tran~latlon dunng my

interviews with the Batemi. ln Nairobi, Pamela Kcen aild her entire family wcre a home and famlly away

from home, providing more than just a Jllace to stry. SImon Mathenge of the Unrvcr~lty

of Nairobi Herbarium quickly and efficiently identified the specimens 1 brought to hlm . • Jll Ken Campbell and Sally Huis of the Serengeti Wildlife Research Centre in the Serengeti National Park wcre incredtbly hospltable and helpful to me when 1 showed up • on thelr doorstep. Thanks for ail your assistance and a wor.derful week of conversations and dJn!1crs.

My field assl~tant, Frederick Sedia, was wonderful company as weil as an

informative gUIde and a keen assistant. His appreciation of my humour made lighter hours of hot days in the sun. Thanks to Juliana, Ayssac and all my other little friends in DigoDigo for their help and for keeping me company. Manfred Oberessel, Maggie and their son Robert at the Wasso HOSpll.:Ù are thanked for their hospitality. They gave me a place to stay, Inedicine when 1 had ma1

sorne u~e for your communities. Asante sana Financial support was provided by a Natural Science and Engineering Research Council (NSERC) scholarship and a Federal Er.vironmental Assessment Research Jffice (FEARO) student research contract.

• IV Table of Contents Abstmct...... • Resume ...... Il Acknowledgements ... 1II

Table of Contents . . . \'

List of Tables...... VIII

List of Figures ...... '. IX Chapter 1. Resource Use and Conscrvation ......

LI Introduction ." ...... 1.2 Problem and Case Study ...... 2 1.3 Objectives ...... J 1.4 Structure of the Thesis ...... 4 1.5 Literature Review ...... 5 1.5.1 The ConservatIOn Crisis ...... 5 1.5.2 Biodiversity: ConservatIOn and Use...... 6 1.5.1 Identification of Priontics ...... 9 1.6 Value of the Results ...... ' .. 13

Chapter 2. Study Arca: Envirollmcnt and Culture ...... 14

2.1 Introduction ...... 14 2.2 Physical Environment ...... 17 2.2.1 Climate ...... 17 2.2.2 Hydrology ...... 17 2.2.3 Vegetation ...... t9 2.3 Cultural History ...... 19 2.3.1 Organizational StructUIi'! ...... 22 2.4 Population Growth ...... 23 2.5 Preliminary InvestigatIons of Change in the Batetnl Arca 2.5.1 Variabihty of Green Vegetation ...... 2fi 2.5.2 Village Changes ...... 2X 2.5.3 Changes in Land Caver ...... 32 2.(. Conclusion ...... , ...... 34

• v Chapter 3. Use of Woody Plants .,...... 35

3.1 IntroductIOn ...... 35 • 3.2 Data Cùilcction ...... 36 3.3 RcsultS ...... 39 :;.3.2 Fuclwood ...... 42 3.3.2 Construr.tlOn Materials ...... , 43 3.3.2 House!lOld Implements ...... , 47 3.3.2. Sei-.. iccs ...... 48 3.4. Discussion ...... , 49 3.4.1 Multipurpose specles ...... , 50 3.4.2 Valucd, Single-Use Species ...... 52 3.4 ConclusIOn ...... 52

Chapter 4. Woody Vegetation Distribution and Abundance ...... 53

4.1 Introduction ...... 53 4.2 Mcthodology ...... 53 4.2.1 Da~ Collection .. 53 4.2.1.1 Random Samples .. 53 4.2.1.2 Addltional Data " 56 4.2.2 Data Analy~ls '" ...... 57 4.2.3 Landcover Map ClaSSification ...... 58 4.2.3.1 Matcnals and Methods ...... 58 i) Materials ...... 60 il) Pre-processing :md image enhancement ...... 60 iii) Geo-referencmg...... 61 iv) ClassIfication ...... 61 v) Error AssC'ssment ...... 62 4.3 ResuIts and Discussions ...... 63 4.3.1 Species Composition and Abundance ...... 63 4.3.2 Random Sites Data ...... 63 4.3.2.1 Classification ...... 67 4.3.2.2 Description of Vegetation types and habItat .. , ...... 67 4.3.2,3 OrdInation ...... 72 4.3.3 Irrigation Chanilels ...... 74 4.3.3 Other specic~ ...... 78 4.3.5 Landcover Map ., ...... 78 4.4 Conclusions ...... 83

• vi Chapter S. Identifying Consen'ation Priol'Ïties

5.1 Introduction ...... • 5.2 Salient Issues ...... 5.3 Methods ...... 5.3.1 Traditional conservation r acticcs ... . 5.3.2 Assigning Quantitative Values ......

lIa') C'L t Ions ...... fP00 li) Use values ...... " ~N 5.3.3 Method for Investigating Endangerment and COllsefv.11 Ion Priorities ...... 5.4 Results and Discussion ...... 5.4.1 TraditlOnal conservation practll'Cs ...... 5.4.2 Use-values .... 5.4.2.1 CItatIOns ...... 5.4.2.2 Value ...... l)X 5.4.2.3 Endangcrrr"'nt and Pnoritics 9X 5.4.3 Assesslllcnt of Mcthods ...... 103 5.5 COllcl usion ...... 104

Chapter 6. Conclusion ......

Referer.ces ...... 1 1 1

Appendix 1 ...... 120

• vii List of Tables Table 2.1 List of Batemi words and their meaning...... 21 • Table 2.2 Population Statistics for Area for 1957, and for DlgoDigo Ward for 1978 and 1988...... 24 Table 2.3 Breakdown of population structure for separate villages and for DigoDlgo Ward...... 25 Table 2.4 NDVI values for the Batemi valley based on a 21 km 2 area...... 27 Table 3.1 Description of Interview groups...... 37 Table 3.2 List of woody species used by the Baterni...... 39 Table 3.3 Species cited as used for firewood. This list is by no means exhausti ve...... 42 Table 3.4 List of species used for construction...... 44 Table 3.5 Species used as implerncnts...... 48 Table 3.6 List of species used for services...... 49 Table 3.7 List of species used for multi-purposes...... 51 Table 4.1 Determination of quadrat size using four sizes of nested quadrats with five replicates...... 54 Table 4.2 Correlation matnx for four bands available for the Batemi area. '" 60 Table 4.3 Training site statistics ...... 62 Table 4.4 Sources of error in the Image Processing and GIS Process ...... 62 Table 4.5 Random sampling species data...... 64 Table 4.6 The ordered TWINSPAN table of sites and species...... 68 Table 4.7 Inventory of Irrigation Channels...... 76 Table 4.8 Species found only along Irrigation Channels...... 78 Table 4.9 Species encountered but not counted in any of the methods...... 79 Table 5.1 Numbers used to calculate values for the various types of use...... 91 Table 5.2 Species indicated as used by the Batemi ...... , . .. 93 Table 5.3 List of values for various construction species based on the two methods of assigning value...... 95

• Vlll List of Figures Figure 2.1 Location of Study ~rea...... 15 • Figure 2.2 A digital elevation model of the Batemi area ...... " 16 Figure 2.3 River and stream network in the Batemi area...... 18 Figure 2.4 An irrigation channel and agricultural fields al the south-end of DigoDigo...... 20

Figure 2.5 NDVI values for 1984 and 1989...... 29

Figure 2.6 NDVI values for the first ten days in M~y for a nine ycar pcnod (1982 to 1991)...... 29

Figure 2.7 Location of traditional DigoDigo village...... 30

Figure 2.8 Location of the Batemi villages...... 31

Figure 2.9 Cleared forest areas in the Batemi valley...... 33

Figure 2.10 Erosion on the flat land of the plains is quitc common in sOllle arcas of the valley...... 34

Figure 3.1 A traditional Batemi hou se...... 45

Figure 3.2 Beehives are placed in the forks of trees ...... 47

Figure 3.3 Euphorhia tirucalli functioning as a live fence...... 50

Figure 4.1. Design of sampling strategy...... 55

Figure 4.2. Flow chart of procedures followed during course of production of I...andcover Map...... 59

Figure 4.3 Species-area curve used to determine samplc size...... 66

Figure 4.4 Distribution of species density levels...... 66

Figure 4.5 Riverine vegetation in the Batemi area...... 70

Figure 4.6 Type 2 vegetation, which is found mostly in hill arcas...... 70

Figure 4.7 Acacia (nrtUis-Balanites aegyptica-Euphorbia candelabrum type vegetation ...... 71 • IX Figure 4.8 Detrended correspondence analysis (DCA) ordination illustrating species space...... , 73 • figure 4.9 Detrended correspondence analysis (DCA) ordination illustrating sample spa~e...... 75

Figure 4.10 Typical irrigation channel vegetation...... 77

Figure 4.11 Landcover map for the Batemi area...... 80

Figure 4.12 Masked landcover map with quadrats and irrigation channels superimposed...... 82

Figure 5.1 Multi-purpose values plotted against availabiIity. 97

Figure 5.2 Construction citations plotted against abundance. 97

Figure 5.3 Construction use-values versus availability ...... 99

Figure 5.4 Construction use-value with consumption fa~tor included...... 99

Figure 5.5 Aggregate use-value plotted against availability ...... 101

Figure 5.6 Availability of medicinal plants...... 101

• x Chapter 1. RelOurœ Use and C'nnserwtion

• Humanity stands at a defining moment in h;story. We are confronted with a perpetuation of disparities within and between nations, a worsening of poverty, hunger, ilI-health and iIliteracy, and the continuing deterioration of the ecosystems on which we dcpend for our-weil being. United Nations, A~enda 21. Prearnble, p.2.5

1.1 Introduction

Biodiversity conservation and protection of human well-being are increasingly seen as being inseparable (WRI et al. 1992). As demands on resources giOw, therc is increased danger of environmental degradation and cultural disintegration. Natural vegetation is important as it contributes to environmental stability and genctic, economic and cultural diversity. White conservation and intcgratcd devcloprncnt strategies are needed to haIt biological impoverishment of the planet (Kapoor-Vijay 1992b), management of natural resources has often been conductcd without local

input and without considering local use patterns, values and knowledge. Conservation

of ecosystems, however, requir~s attention to the cultural as weil as biophysicdl landscape of an drea. Preservation without consideration of local inhabitants has not worked, as witnessed by innumerable contlicts around parks. Awareness of local needs, values and knowledge is essential for identifying problem areas and for implementing successful conservation strategies. Input from ail levels of society can facilitate the fin ding of sustainable solutions and alternative conservation strategies.

An integrated approach to the 'exploitation and conservation of resources is in the long-term interest of people" (Johns and Kokwaro 1991) .

• 1 1.2 Problem and OIse Study increasingly, conservation and development initiatives are being focused on a

• local sc31c, as evidenced in approaches such as integrated conservation and devclopment strategies (Brown and Wyckoff-Baird 1992). In Sale and Loliondo Divisions in Ngorongoro District, Tanzania, there is a strong desire for the development and implementation of a regional, sustainable utilization plan, with stmng local participation. The area, inhabited mainly by Maasai pastoralists and Batemi agropastoralists, is semi-arid, subject to temporal and spatial variability in rainfall, and unable for the most part to support high-density populations. As with many groups in remote, marginal areas, the Batemi and their pastoralist neighbours, the Maasai, still follow an essentially traditional way of life. Both groups rely heavily on the natural ecosystem. Changes can have severe repercussions on the well-being of communities, not only through impacts on food and medicine, but also by changing everyday cultural practices. To ensure that community needs and values are addressed within the context of changing environmental and socioeconomic conditions, a local non-governmental organization (NGO), Korongoro Integrated Peoples Oriented to Conservation (KIPOC, meaning 'we shaH recover" in the Maasai language), has been formed with the endorsement of the Ngorongoro District Council. The Ngorongoro District Council, KIPOC and local communities are in the process of formulating a land use plan in relation to the pastoral system. The Serengeti Regional Conservation Strategy (SRCS) has carried out aerial surveys and will be preparing maps of land use in the Loliondo area to aid in this project. Land claim r.egotiations underway in the region are an added source of tension and underscore the importance of resource and conservation planning.

• 2 Directly connected to these plans for a local conservation stratcgy is a specific focus on food and the health of local people. A health and nutrition project planncd • by the Ngorongoro District Council, KIPOC and MacDonald C.ampus of McGill

University, in collaboration with the Institute of Traditional Medicine (ITM) and the Tanzania Food and Nutrition Centre, will investigate the nutritional status of the

Maasai and Batemi people in Sale and Loliondo Divisions. The project will includ~

an analysis of the use of wild plant resources and their nutritional and mcdidnal

value. The research undertaken for this thesis focuses on the use, distribution and conservation of woody vegetation that is integTal to the human community. A

preliminary ethnobotanical survey conducted in the Batemi area showcd many local

woody speciec; as useful (Johns 1992). A systematic study of the general st~ tus of

woody vegetation in the area and the distribution and abundancc of useful woody

species can provide valuable information on the biological state of these resourccs, areas of actual or potential vulnerability, requirements for plant r;onservation and implications for local communities. Recording use of vegetation (used versus unused

components of the environment), mapping distribution (rela~ed to availability and

territorial questions) and assigning values (to recognize importance of conservation)

are a1l important steps towards achieving "sustainable development" planning.

1.3 Objectives The overall purpose of this research is to assist in the collection of bascline

data for use in local conservation and management planning for the Batemi area and

to explore methods for identifying conservation priorities. Specific objectives are to:

1) investigate local use of vegetation • 3 2) study the abundance and distribution of woody vegetation in the area • 3) experiment with assigning use-values to species and with using these values to identify conservation priorities.

1.4 Structure of the Thelis Chapter 2 presents basic physical and cultural factors. Population densities

and resourees of value ta the Batemi are discussed. The variability of green

vegetation is investigated using National Oceanic and Atmospheric Administration

(NOM) advanced very high resoJution radiometer (AVHRR) satellite data. Land use and land cover changes are analyzed and iIIustrated using the Geograpbical Resource Analysis Support System (GRASS) Geographical Information System

(GIS). Chapter 3 presents ethnobotanical data on non-medicinal and non-food uses of woody species which were collected during June-July 1992 and August 1992. These data are suppJemented by medicinaJ and food data coUected by Johns (n.d.a, n.d.b).

Chapter 4 contains the biogeographical data collected using a random

sampling method, with additional data from comprehensive inventories along

irrigation channels. A land coyer map for the area was produced on GRASS using

Landsat Thematic Mapper (TM) digital data.

Chapter 5 explores data of pertinence to establishing conservation priorities. Use-values are assigned to species used by the Batemi. This information is then used

in conjunction with the data on abundance to investigate the vulnerability of species.

These data, based on categories of use, are employed to identify key socioeconomic

species and the conservation priorities amongst them.

• 4 1.S Uterature Revicw • There is worldwide pressure on the biophysical environment due to increasing human population and technological demands. Global responses to the conservation crisis are evident. Recent world events include the June 1992 United Nations Conference on Environment and Development (UNCED, or the Earth Summit), a follow up to the World Commission on Environment and Devclopment, and 1993 is

the United Nations (UN) Year of the World's Indigenous Penples. Literature

outlining the crisis and recer..t approaches are discussed below, with a foeus on rural,

semi-arid areas and indigenous peoples.

1.5.1 The Conservation Crisis The degradation of land is invariahly accompanied by the degradation of human well-being and social prospects (Biswas 1979, 260).

Ever-increasing demands on the biophysical environment are a source of

concern as ecosystem integrity and viability are threatened either through over-use

or misuse. As the biophysical environment is degraded, there are lIsually negative impacts for the humans who rely on those resources. Impacts are often experienced

more immediately in traditional or subsistence environments, where people are

directly dependent on the resources surrounding them. As economÎc and

technological circumstances change and populations grow, weil adapted traditional

practices may breakdown or excessive pressure may be put on fragile resources. A number of studies in Africa have documented the degradation of natural

systems due to misuse or overuse (Dorm-Adzobu 1982; Newby and Grcttenberger

1986). "Logging for export, clearing for agriculture and cutting for fuelwood ail

consume trees for human benefitll (Timberlake 1986, 103; cf. Rowe et al. 1992) . • 5 Fuelwood u~e is one of the most ecologically destructive uses of woody plants • (Bowandet 1986, ] 987), but other indigenous uses can also damage plant communities. Cutting of trees for construction material can have severe repercussions. Several species of trees in the Usambara region of Tanzania have been severely depleted because of demands for building (Fleuret 1980). Clearing for

agriculture also makes inroads into remainin.g forest areas. Even gathering clIn' nave

serious effects, especially as demands grow. Vasque;,~ and Gentry (1989) round that there were dangers of destruction of trees during harvesting in the Iquntos area of Peru. Grazing and browsing by domestic an;mals are other factors that may have serious repercussions for local environments, especially in fragile, slemi-arid and arid regions (Palmberg 1991). Lamprey(1984) documents the impact of Maasai pastoralism (livestock and seulement distributions) on vegetation patterns and distribution in the Maasai Mara area in Kenya. In general, the structure and composition of woody vegetation in savanna or wood land enviromnents tends to change WÎth increases in grazing and browsing. Usually the woody species composition increases with grazing as the decrease in the grass layer leaves more moisture available for woody species (Skarpe 1990a, 1990b). The browsing of species can result in higher woody species mortality (Reuss and Halter 1991).

1.5.2 Biodiversity: Conservation and Use The increasing degradation of the biophysical environment and evidence of higher rates of species extinction (WRI et al. 1992) ha,'e underlined the need to conserve biological diversity by insuring that use is sustainable. Biodiversity ïs defined

• 6 as "ail species of plants, animais and micro-organisms and the ecosystems and • processes of which they are a part" (Kapoor-Vijay 1992a). In a review of the biodiversity literature, three main points in the biodiversity debate are central:

conservation, use and equity. The World Conservation Union's (IUCN) World Conservation Strate.:y (1980) was one of the first international policy statements to cali for slistainable lise of ecological resources. This document defined conservation as: The management of human use of the biosphere so that it may yield the greatest sustainable benefit to present gcncrations while maintaining its potential to meet the needs and aspirations of future generatior.s. This conservation is positive, embracing preservation, maintenance, sustainabIe utilization, restoration, and enhancemcnt of the natural environment (JUCN 1980). The World Commission on Environment =md Development (WCED) and the United Nations Conference on Environment and Development (UNCED) have further focused global attention on these issues. The conservation and fustainable use of biological diversity was central to the UNCED conference. A&enda 21 (UNCED 1992a) , the major document arising from the conference deals with a numbcr of important environment and development issues, including the conservation of

biodiversity (Chapter 15). The Convention on Biolo~ical Diversity (UNCED 1992b), developed uoder the auspices of UNEP and the IUCN was signed by Most member nations at the conference and more recently the U.S.A signified its intention to sign.

There are also a number of otber major documents and initiatives focusing on

biodiversity conservation. The Global Biodiversity Strate~ (WRI et al. 19(2) aims to outline a strategy for saving, studying, and using biodiversity sustainably and equitably. The sustainable and equitable use of biodiversity is defined as "husbanding biologicaI resources so that tbey la st indefinitely, making sure that biodiversity is used to improve the human condition, and seeing that these resources are shared • 7 equitably'(WRI et al. 1992, 13). 00 a practical level, the Commonwealth Science • Council's (CSC) Biological Diversity and Genetic Resources (BDGR) programme seeks to devclop practical plans geared towards conserving biodiversity and th us ensuring sustainable development (Kapoor-Vijay 1992a). Interwoven with the sustainable use debate is the issue of equitable use. Use

and development of ecological resources must he people-centred as weil as conservation-based:

Action to conserve biodiversity must he planned and implemented at a scale determined by ecological and social criteria. The focus of activity must be where people live and work, as well as in protected wildland areas (WRI et al. 1992, 23). Although preserved areas, where human intervention is kept to a minimum, are still considered central to conservation aims, the focus has broadened to include social and cultural issues. Guroll (1992, 365) states: Conservation is not just biology and must be an interdisciplinary effort. Conservation must become an integrative effort to treat the landscape as a life-support system for economic and biological diversity. The CSC's programme portrays a similar approach: ''The conservation of biological

wealth is Ilot simply a traditional protection agenda, but a scientific, economic, social, political and development issue"(Kapoor-Vijay 1992a, 6).

Local peoples and national economies need to he able to derive social and economic benefits from the conservation of biodiversity (NRC 1992). Carroll (1992, 363) states that "patterns of use must be considered along with the characteristic of

the local ecosystem in any long-term attempt at management". This type of outlook is significantly different from that of years ago, when protected areas or parks were set up without real consideration for the impact on local populations.

• 8 1.5.3 Identification of Priorities • As discussed above, local resource use, knowlcdge and culture systems have become a centrai issue in the conservation and developml'nt debate. Therc al e a

variety of reasons for this, incJuding: the nced to rccoglllze use patterns; the

importance of that local knowledge as a data source, espccially in remoll', or

marginal areas which are not weil studied by western scicnce; and the mie that this information can therefore play in designmg successful conservation strategIes.

i) The first compone nt of this issue deals with the direct rehance of rural and

indigenous groups on biological resources for meeting daily necessities, with the necd

ta recognize particular uses of each community or region.

For a number of societies, gathering is still an important activity; many agropastoral or subsistence farming groups "stIll obtain a significant portion of ...

subsistence requirements from the ecvsystems that cmbed and SUi round the

agricultural plots"(Altieri et al. 1987). Use of natural ecosystems, or modified

versions of them, provides "a d~versity of products through a strdtegy of multiple

usell(Altieri et al. 1987). Grivetti's (1978a, 1978b) study of the Tswana of the Kalahari reveals the diversification ai the food base ansing from plant gathering.

Fleuret's (1979, 1980) studies in the Usambara mountains of Tanzania underscores the important nutritional and economic role that wild plants can have for traditional

societies (see also FAO 1983, 1988). Vegetation gathering has an economic and

ecological basis; it proviJes essential supplies of food, raw materials ct cetera aDd

also has strong cultural tradition (A1tieri et al. 1987). Traditional rnedicines from

indigenous vegetation provides the primary health care needs for 80 percent of people in developing countries (Farnsworth 1988) .

• 9 Woody vegetation can play a particularly important role in the economic, • social and cultural life of mdigenous people. Woody vegetation provides a variety of uscful products, such as construction materials, food, medicine, fuel, fodder, and

also ~erves as a harrier against environmental degradation (see Altieri et al. 1987;

Douthwaite 1987; Newhyand Grettenberger 1986; Palmberg 1992; Reid et al. 1990). Many woody species in East Africa have also been identified as playing an important economic role within local cultures (Pichi-Sermolli 1955). In fact. for many suhsistence farmers, ''trees are often the only source of sorne of the necessities of

11 life. A~ the trees disappear, these essential products become scarcer... (Timberlake 1986, 1] 2). Studies such as Boom's (1989), which shows that the Chacobo of Brazil utilize 82% of species and 95% of individual trees, illustra te the breadth of

indigcnous use of IInatural ll vegetation.

Amongst the range of resources in a given area, there may be sorne that are particularly valuable or central ta the economic, cultural or social Iife. The identification of these Valued Ecosystem Components (VECs) (Be an lands and Duinker ]983) or key socioeconomic species (Kapoor-Vijay 1992b) can be helpful in

identifying priority issues. This type of approach is being adopted recently, él'.: p.vident in the Commonwealth Science Council's programme's list of objectives. There are two concerning the identification of key species: 1) survey and authentication of species of socioeconomic value and 2) Identification of key species for conservation and development (Kapoor-Vijay 1992a, 13). "Key" species are termed either 'ecological key species'(which play a key ecological role) or 'service species', which

"make contributions to people's social and economic well-being. Key service species are important with respect to certain categories of use, such as commodities, genetic resources, cultural value or environmental management (Kapoor-Vijay 1992a, 45) .

• 10 Both types are considered life-support species. Frics' (1991) recorllmcndattons for • a research strategy for study of East African forc~ts foeus on ~tudyl\1!:! local 1I~l' ot species as weil as conductI;lg basic II1ventone~. Recl'nt L'thnohotal1lcal stll'Jles

(Pinedo-Vasquez et al. 1990; Pranœ et al. 19H7) haw atlL'l11ptl'd to t.'~tahh~h lISL'­

values for locally valued plants in arder to identlfy conservation pnontles. For

example, Prance et al. (1987) found that certain plant familles 111 Âmazol1la should

have high priority for conservation and that certain types of forcst should he a hlgh

priority habitat type.

ii) As weil as the basic importance of addressing local needs and valucs, therc IS

the value of local knowledge and conservation practices as vital data ·,ourccs. The

cÛ~lsideration and incorporation of local values and knowledgc is crucial as loeals

usually have in-depth knowledge about their environments that outSiders will not

have. They have intimate knowledge of cycles, of environmental changes, and

frequently of ecologlcal proccsses. Johannes and Hatchcr(1986) point out that

traditional practices hnd values are often a rich rcpository of consuvatlon policy 111

terms of well-developed systems of knowledge and practices specifically adaptcd for

the area.

Various studies detail local or indigenous knowledge and its applIcation to

conservation and resource management. Many ethnobotanists, anthropologlsts and

cultural geographers have examined indigenous classification ~ystcms (sec Berlin ct

al 1974; Nabhan et al. 1991; Nietschmann 1973; Toledo ]991), cxploring the dcpth

of local knowledge and means of organizing data. Many argue that indigenous

groups are not mere resource foragers but are resource managers as weil (sel' AIcorn

1989; Oldfield and Alcorn 1991a), although Dasmann (1991) disputes the necd to

• 11 dirfer between use and management. Many recent studies do show, however, that • many groups are not merely responding ta given environmental Iimits, but cIearly manipulate and manage critical resources. Relevantexamples include Alcorn's (1989) study of the management of agroecosystems in Peru and Mexico and Denevan and Padoch's (1988) work with the Bora Indians in Peru. A particularly interesting example is the Kayapo of Brazil, who practice wide-ranging resource management, incIuding such subtle, trall-side management of vegetation that it appears as natural

to outsiders (see Anderson and Posey 1989; Posey 1983, 1984).

The application of this type of local information in conservation strategies can

he extremely usefu) and valuable (Brokensha et al. 1980; Klee 1980). Local knowledge systems can yield new ideas about conservation and management of valuable resources and identify new biotic resources for utilization (NRC 1992). Reid

et al. (1990) recommend gathering of more information on local uses, in arder to help improve traditional land management practices in the Tamaulipan thomscrub of Mexico. Besides the fact that local knowledge can improve the management and conservation process through increased information, there is also the fact that consideration of local knowledge systems and values will make conservation strategies

and management plans more acceptable to local communities. Johannes and Hatcher

(1986, 379) state,

Modern management regimes in which tradition al management cu~toms are recognized and incorporated (where practical) are Iikely to gain greater local support and thus be easier to enforœ. Traditional authority and indigenous environmental regulations often cany more weight ... than do remote government edicts.

Plans are more Iikely to be accepted and thus to succeed if they refleet local values,

needs and knowledge. Conservation efforts will ultimately fail if they do not integrate • 12 • local needs and prevailing land use practices (Oldfield and A1corn 1991h) . 1.6 Value of the Results This the sis attempts to relate practical fieldwork on the use and distribution of native woody species to the process of establishing conservation priorities. This

work is supported by the local communities and il is hoped that it will be userul 10

them in i) systematically documenting valued species, ii) defining the territorial cxtcnt

of their resource base, and iii) developing a conservation strategy. As one of the main concerns of this research is to produce useful information to supplement local knowledge, the final results of the rescarch and any

recommendations will he presented to the Ngorongoro District Council, KI poe and local communities, and the Tanzania Commission for Science and Technology for

input into land use plans. AlI research findings will also he presented to the Institutc

of Traditional Medicine and the Tanzania Food and Nutrition Centre.

ft is hoped that documenting the importance of local plant communities will help groups such as KIPOC ensure that, whatever the ecological stress of cureent

development pressures, the "we will recover" ambition will he possible. Il is also

hoped that the thesis will make sorne contribution to the dialogue on conservation

and development.

• 13 • CulpfCr 2. Study Arca: Enviromnent and Culture 2.1 Introduction

The Baterni are a Bantu agropastoral group, who in habit an area surrounded

by Maasai tribal territory. Unlike their neighbours the Maasai, this group has not

been widely studied. Besides an ethnographie study undertaken ;n the late 1950s

(Gray 1963), the only Iiterature available are obscure Tanzanian goverument reports

which briefly diseuss the Batemi (Fosberg 1957 in Gray 1963). More recently

ethnobotanical work (Johns n.d.a, n.d.b) and sorne work on irrigation (Potanski n.d.)

have been undertaken in the area.

The group has traditionally existed on an almost completely self-sufficient

basis, practising two forms of subsistence: stock raising and cultivation by irrigation

(Gray 1963). It is thought they have been located in the area for at Jeast one

hundred and fifty years (Gray 1963). As a subsistence agropastoraJ group, the

Batemi rely heavily on traditional resources for their livelihood. Their well-being is

therefore dependent on the state of the environment, and on their ability to retain

a sustainable relationship with it. The Batemi valley faces most of the pressures that

confront many rural areas in semi·arid regions, including a grc.wing population,

declining resources, changing cultural values and imposition of external management

structures from a national level.

The study area is in Sale Division, Ngorongoro District, in the northwestem

section of Tanzania (Figure 2.1). The Baterni villages (six, plus sorne sub·villages) are

located to the east of :he Rift Valley, to the north of the Ngorongoro Conservation • 14 Figure 2.1 Location of Study area.

- -- T ) , 1 • )'

hdls

'. S"ronrrd

Sll~lJtnaland Mor"

-3

1 O~-~30Km

Source: Sinclair 1979. • - STUDY AREA

Area and about twenty kilometres south of the Kenyan border. Three of Sale

Division's œnsus wards (DigoDigo, Oldonyosambu and Sale) are inhahitcd almnst

exclusively by the Batemi. This study is restricted to DigoDigo ward, the central and

most densely populated of the three wards. Four of the six main Batcmi villages

(DigoDigo, Sarnunge, Mugholo and Kisangiro) are located in this ward .

• 15 The main part of DigoDigo Ward is a valley, bordered byescarpments to the • north and various hill ranges to the east and west (Figure 2.2). On the south side, there is a general drop in elevation towards the Sale Plain. Elevations range from

about 1200 m above sea level on the valley floor to 2000 m in the hms north of th,~

valley.

This chapter will provide an introduction to the physical and cultural

envimnment and the reJationship between t}le two components. It examines

variability in bioproductivity over time and space. Changes in the valley in tenns of ._

Figure 2.2 A digital elevation model of the Batemi area. The image shawn is a 2-4- 7 band composite from Landsat Thematic Mapper digital data. The viewing site is from the south-west corner at an angle of 30 degrees. The green represents dense vegetation (thicket or wood land). The white mainly consists of the villages, agricultural fields, and areas of wooded grassland and scattered trees. The pink areas • are areas of more open wood/and.

• 16 land use patterns and community settlements ace also examined. The data in titis • chapter, except those attributed to other sources, are from the author's observations and interviews.

2.2 Pbyaica1 Bnvironment

2.2.1 Climate

A1though there is no local weatherstation at present, rainfall data were collected in the late 19408 and early 1950s and reveal a great temporal and spatial variability. Eight years of data gave an average annual rainfall of 412 mm, with only

one year exceeding 660 mm and two years exceeding 440 mm (Gray 1963). The

peaks of the rains are in April and January with sorne rain falling in September and

October. The area falls within 400-600 mm isohyet of average annual rainfall

(Tamsett 1969 in Porter 1976; cf. with White 1983) and is classed as semi-arid,

defined by Christiansson et al. (1991) as an average annual rainfall of 250-500 mm

and at least a 7.5 month dry period.

2.2.2 Hydroloi,Y

The Batemi area is part of an interior drainage basin (Atlas of Tanzania

1967). The Loliondo highlands are the dividing tine between those rivers that drain towards Lake Victoria and thase towards Lake Natron. Figure 2.3 depicts the rivers

and streams in the area. Natural springs are scattered along the base of the

escarpment on the north side of the valley.

• 17 • • •

Scale 1:75,000 j 1 Wynet Smith 1993 o 5KM Legend: - Rivers and streams 9766000.5 --- - Elevation (m) UTM Region: 797000.5 813000.5 9757000.5 2.2.3 Ve~etation • There has been no published study of the vegetation in the Batemi area on a local scale. A general idea of composition or type of vegetation is availahlc from

smaller scale maps and reports (White 1983; Und and Morrison 1974; Pratt et il/.

1966; Trapnell and Langdale-Brown 1969). In terms of phytochoria or biogcographic region, the Batemi area is situated in the Somalia-Maasai rcgion of cndcmisOi (Wtnte

1983). The major vegetation cover in this region is deciduous bush land and thicket,

specifically, Acacia-Commiphora deciduous bush land and thicket (White 1983). This

vegetation has been tcrmed Commiphora bushland by Trapnell and Langdalc-Brown

(1969) and woodcd steppe with abundant Acacia and Cummiphora spccies by Kcay et al. (1959).

2.3 Cultural Hiatory

The semi-arid nature of the environment makes the arca suitablc for two

forms of exploitation: stock-raising and cultivation by irrigation. As agropastoralists,

the Batemi utilize most components of their environment, including: land and wilter for agriculture; land for grazing; and vegetation resources from the forcsts and fields

for various types of materials (cf. Gray 1963). These uses are by no means mutually

exclusive.

Local aridity means that springs, streams and rivers are the source of life for

the Batemi. The Batemi have manipulated the various elements of the nattlral

ecosystem to create a system of irrigation that has functioned sufficicntly weil tn support their population (Gray 1963). For example, the village of DigoDigo waters

many fields from two irrigation channels and one stream (Figure 2.4) .

• 19 Figure 2.4 An irrigation channel and agricultural fields at the south-end of DigoDigo. The irrigation channel cutting across the landscape has its source in a spring and a srnall stream. The second row of less dense vegetation to the right is along the stream. A second irrigation channel is partially visible in the lower right-hand corner • of the photograph.

•

The traditional practice of irrigation in East Africa is quite unusual. At the

time Gray (1963) wrote his ethnography there were only four groups practising

irrigated agriculture in East Africa. Il is hypothesized by Gray (1963) that the Batemi

system is based on an ancient irrigation culture, and that the Batemi are either the

descendants of those who settled in the area with tbis knowledge or that tbey

inherited the practice from their predecessors in the area. Many of the irrigation

channels in the area stem from springs; the remaining ones are offshoots of river • 20 tributaries. Oldonyosambu, a village to the east of DigoDigo Ward relies solely on • a river passing through the village as its source of water (cf. Gray 1963). Streams and springs emerge from the hills, and the villages are ccntrcd mostly

on the northern side of the valley, close to the main water sources. The springs now

ail year round, but most of the streams are seasonal, f10wing only in the rainy scason.

Stretching south frorn the villages is valley bottom and plain. Most of the northcrn

part of the plain is used for agriculture and Iittle "natura)" vegetation remains. A

mixture of crops are grown, and there are both irrigated and non-irrigated arcas of

cultivation. The irrigated fields are known as hura (Table 2.1), and were traditionally

plan~ed in the dry season (around September). The dry-land agricultural fields arc

known as magare and were traditionally planted in the rainy season, with cach field

only being planted every second year (Gray 1963). Intercropping of multiple laycrs

is common. The variety of crops includes legumes, cassava, sorghum, maizc and also

various other more recent crops such as onion and tomaloes (Johns n.d.b). A

number of fruit trees (papaya, citrus) are also grown by sorne people.

Table 21 List of Batemi words and their meaning. Ratemi word Meaning Bwelo - plain or valley tlOor Hura - dry-season agricultural fields (irrigated) Magare - wet-season fields Shamba - garden or small agricultural field Wenamije - clan with hereditary rights to water systems

• 21 Further south on the plain are drier areas where the lack of streams and • springs prevent irrigation. In the se are as, only dry-land cuItivation is conducted. The Samunge sub-village of Eyasi is an exception, as there are streams that permit irrigation. The major land use in this area, however, is grazing. The Batemi colle ct a large percentage of materials from the natural plant communities surrounding them. Gathering is an important part of their culture and subsistence strategy.

2.3.1 Ora:anizational Structure In the Batemi area, traditional social organization was based on clans (Gray

1963). There were clans in each village, with each clan having a certain place within

a hierarchy but, at present, there are national structures imposed upon the traditional

local system. Village leaders and secretaries are Government or Communist Party representatives. They are officially responsible for making decisions in their

respective villages. Because the traditional Batemi groups are still very much in place, there are occasionally disputes between the different levels of authority. Each

village head reports to the Division secretary, who is responsible for the five wards

in Sale Division. Sorne laws, such as those regarding forestry resources, are national

in origin and are enforced by the Division secretary and the village leaders. But

traditional laws, such as the Batemi prohibition against cutting along irrigation channels (see Chapter 5), are not interfered with and are not subsumed under nationallaw.

The springs used for irrigation are regarded as sacred (Gray 1963, 50-52).

Traditionally, the irrigation system has been under communal control of a village

composed of several clans, and this system has been in place at least since the 1800s

• 22 (Gray 1963). This system is still mostly in place, with the Wenamije. the group will\;.; • each village who has hereditary rights, still controlling final decisions over irrigation. The village of Samunge is one exception; here the village chalrman has follnwl~d

Tanzanian governrnent law that states that therc should he a water committcc in each

Tanzanian village. Therefore, control of the irrigation system in this village IS now

under his control and not the traditional Wenamije clan!. The bask prillciplcs of the

irrigation system still apply, with local communal assistance still an important

compone nt of the functioning of the system.

2.4 Population Growth

Population growth "affect[s] the demands on living space and other resourccs"

(Kasperson et al. 1991,47). The Batemi population in 1957 ('onsisted of 2063 males

and 2325 females for a total of 4388 people (Government of Tanzania 1957). The

1967 census indicates a population of 5,071 (Governmcnt of Tanzania 1967) for the

area but this data is not directly comparable ta the 1978 and 1988 data as the figures

are for different census areas. For 1978, the population size of DigoDigo Ward alone

was 5350 and for 1988 it was 6753 (Government of Tanzania 1978, 1988). Including

Sale (1030) and Oldonyosambu (2069) wards, there was a total of 9,852 in the entire

Batemi area. The population has therefore teen growing steadily for the last 30

years (Table 2.2).

1 Gray (1963) noted that Samunge had more contact with the outside world than the other villages. Whether this is a factor in the difference between the present practices in Samunge and the other three villages is not c1ear. • 23 Table 2.2 Population Statistics for Area for 1957, and for Dig0Digo W:!rd for 1978 and 1988. Population Size • 1 :J i Census Year Male Female -IOtal 1 1 1957 2063 2325 4388 1967 5071* 1978 2523 2827 5350 1988 3033 3720 6753

Source: Uovernment of "lanzama 19j7 1967, lYRS and l~~.

* not directly comparable to 1978 and 1988 data.

(Table 2.3), but this includes the sub-villages of Mditu, Mgero and Mgundu.

Kisangiro is the least populated village with only 1119 people.

As can he seen from the statistics in Table 2.3, the population is overwhelming young, with 36.5% (2462) of the population under 9, 50.7% (3421) under 14, another

17% between 15 and 24 and a further 9.76% between 25 and 34. In other words,

78% of the population i!J under the age of 35. This indicates an increasing pressure

on the local resources and will have implications for sustainable resource planning.

There is also a disproportionate number of females to males, 3720 to 3033 individuals respectively. The age groups under 14 are roughly gender balanced. The

majority of the imbalance oceurs in the young adult and adult populations, between

the ages of 15 and 54 (Table 2.3). The likelyexplanation is that men are woring

outside the area, either in cities or for others in the surrounding region informai

comments by various people in the valley supported this explanation. The effects of

• 24 Table 2.3 Breakdown of population structure for separate villages and for DigoDigo • Ward. AGE Sex 0-4 5-9 10-14 15-24 25-34 35-44 45-54 55-64 65+ Total Samunge Male 231 222 177 127 113 54 44 47 71 1O&i Female 256 258 184 260 158 102 85 51 72 1426 TOTAL 287 480 361 387 271 156 129 98 143 2512

DigoDigo Male 128 127 133 137 71 39 48 44 46 773 Female 144 166 135 199 103 80 45 60 26 958 TOTAL 272 293 268 336 174 119 93 104 72 1731

Mugholo Male 133 131 81 74 62 41 38 24 36 620 Female 149 148 87 131 73 58 43 34 48 771 TOTAL 282 279 168 205 13S 99 81 58 84 1391

Kisangiro Male 106 83 89 107 54 47 21 21 26 554 Female 87 93 73 124 65 45 33 31 14 565 TOTAL 193 176 162 231 119 92 54 52 40 1119

Total for Male 598 563 480 445 300 181 151 136 179 3033 Ward Female 636 665 479 714 399 285 206 176 160 3720 TOTAL 1234 1228 959 1159 699 466 357 312 339 6753

Source: Government of Tanzania 1988.

tbis gender imbalance are most likely felt by the women, who may have extra work

or more decisions to make about cultivation than they formerly did. This issue would

he important area ta research more in the future.

2.S Preliminary Investigations of Change in the Batemi Alea Along with a growing population, there have been a number of changes to the

physical environment. These include ongoing variabiJity in soil moisturc availability

and green vegetation, changes in village locations, and encroachments on the bush

areas, particularly along the escarpment. The list of materials used to conduct thcsc • 25 • analyses, and their sources, are listed in Appendix 1. 2.5.1 Variability of Green Ve2etation The advanced very high resolution radiometer (AVHRR) carried on the current National Oceanic and Atmospheric Administration (NOAA) satellites provides data on local environmental conditions that affect crop growth and reflect current status of vegetation. A VHRR has been used extensively to monitor vegetation condition and estimate biomass (see Justice 1986 and Prince and Justice

1991 in Hutchinson 1991). Vegetation condition and amount can he estimated by combining the red and near infra-red (NIR) spectral bands in the following manner

[NIR-Red]/(NIR + Red] to obtain a normalized difference vegetation index (NOVI) (Hutchinson 1991; Prince 1986). The index values vary, principally as a function of photosynthetic activity of vegetation (Tucker 1979 and Prince et al. 1991 in

Hutchinson 1991).

NOAA, A VHRR NOVI data from the United States Agency for International

Development, Famine Early Warning System (USAIO/FEWS) project were used to

examine the temporal variability of green vegetation in the Batemi valley for the period from 1983-1991. This data is compiled from daily information into ten-day

periods (decadels), resulting in three images each month (Prince 1986). A 21 km2 area (or nine pixels of seven km resolution) was extracted from the data set available

at the Serengeti Wildlife Research Institute using a central coordinate of 2°10' south

and 35°45' east. The data were used to compare seasonal and annual variation.

As can he seen from the NDVI values, there is a great deal of temporal fluctuation in the green vegetation in the Batemi area (Table 2.4). This fluctuation not only covers the course of a year but a]so occurs between the matched periods for

• 26 Table 2.4 NOVI values for the Batemi valley based on a 21 km 2 arca .

8) • Pcriod 'lime tI2 114 es 1!6 87 ~ 119 90 A..,n~ 1 Jllluory 0.29 0 0.42 0..12 0.29 0.49 0.27 c.14 0. \5 o.~". o.,z" 2 Jllluory 0.27 0.3 0.3 0.32 0.311 0.49 0.27 0.4 OS7 0..1 o.J6 3 JUlUOry 0.29 0.3\ 0.4\ 0.2 0.311 0.53 G.4\ 0.46 0.5 0.2.\ 0.374 4 February 0.32 0.3 0.43 0.26 0.14 0.4 0.46 0.57 0.46 0.19 0.1'1.1 S FeIInIIry 0.3\ 0.\9 0.311 0.23 0.14 0.5 0.44 0.58 0,,)9 0.42 0.3711 6 Febniary 0.311 0.37 0.36 0.0 0.24 0.45 0.31 0.52 0..1 0.\ 0'J(M\ 7 MII'CtI 0.41 0.29 0.32 0.44 0.24 0.36 0.14 0.46 o.S4 Il \ O,n 8 MIR:b US 0.23 0.34 0.42 0.3 0.34 0.2 0.47 0,S6 0.27 0.348 9 MIR:b 0.36 0.22 0.4 0.47 0.25 0.42 0.45 0.41 0.6\ 0.21 o.. 10 Ap1I 0.38 0.23 G.32 0.48 0.22 0.37 0.411 0.47 0 0.429 11 Ap1I 0.33 0.15 0.45 0.49 0.37 0.4 0.5 0.56 0.57 O,J:tII 12 Ap1I 0.44 0.16 0.46 0.5 0.37 0.45 0.45 0.46 0,st1 0.424 13 Moy 0.44 0.4 0.51 0.51 0.4 0.45 0.54 0.47 o,S9 0.43 14 Moy 0.5 0.4\ 0.49 0.54 0.4\ 0.411 0.46 0.48 0.53 0,411\ 15 May 0.43 0.311 0.44 0.5\ 0.46 0.33 0.43 0.49 0.52 0.4711 16 June 0.43 0.27 0.34 0.0 0.46 0.27 0.311 0.55 0.49 0.443 17 J_ 0.39 0.29 0.3\ 0.38 0.43 0.36 G.3 G.42 0.48 o.4IU 111 J_ o.J4 G.2 o.l9 0.29 0.38 0.29 G.3 0.4 0.45 0.373 19 JIIly 0.211 0.\6 0.2 o.J\ 0.3\ 0.216 0.216 0.34 0 0.3\7 20 JIIIy 0.26 0.27 0.17 0.26 Q.216 0.27 0.17 0.3\ 0 Q.2J6 21 JIIIy 0.23 0.23 0.2\ 0.23 G.2 0.19 0.2 0.2 0.32 0.219 22 Aupt 0.\9 0.24 G.l7 0.2\ 0.211 0.\6 0,l4 0.26 0.2\ 0.21.6 23 Aupt 0.16 0.14 0.\ 0.\9 0.24 0.\8 U8 0.17 0.\6 0.218 24 Aupt 0.15 0.\6 G.l4 0.\8 8.23 0.16 0.26 0.13 o,U 0.\8 2S SeplaDb. 0.\6 0.\4 0.17 0.\3 0.22 0.\8 0.2 0.\6 0.23 0.\7\ 216 SeplaDb. 0.16 0.13 o.U 0.\6 0.2\ 0.17 0.2 0.\8 0.23 0.\77 27 SeplaDb. 0.17 0.\ o,U 0.\7 0.\9 G.l8 0.15 0.1 0.l4 0.\16

211 0cI0ber 0.2\ 0.00 0.07 0.\6 0.\9 G.l1I 0.07 ~I' 0.2 0.\58 29 0cI0ber 0.2 0.13 U2 0.16 0.17 0.\11 o,U 0.:3 0.17 0.1. JO 0cI0ber 0.24 0.16 G.I\ 0.\11 O,Zl 0.13 0.16 '.111 0.111 0.1t6 31 NCMIIIber G.33 0.11 0.12 0.1' o.\S 0.14 0.23 0.2 0.111 ..172 JZ N-"er G.33 0.13 o.zl o.J o.z 0.24 G.l8 0.22 0.23 1.111

NIMMa' 0 0.17 o.J4 0 0.23 Q.31 f" 0.1 0.23 0.227 "34 ~ 0.46 0.18 Q.31 o.JS 0.24 Q.37 1.21 0.22 0.\4 UN JS Deceatber 0.45 0.16 0.47 o.JS 0.42 Q.36 0.23 0.27 0.26 1.216 36 Daoa.IIIr U3 0Ji6 U6 l.l4 o.. U6 .., 1.22 .., t.» A..... t.3O'JS 1.2133 Q.1914 l.Ja7S '*' Q.3167 um 1.0»711 0.3367 Q.3311

Source: NOAA, A VHRR NOVI data.

• Zeros indicate missing values . • different years. Annual variation is quite extreme; Figure 2.5 illustrates the range in values for two years (1984 and 1989) and for the average over the ten year period. • There is tremendous intra-Yf:ar and inter-year variation. Figure 2.6 ilIustrates the range in values for early May for the ten-year period. This time of year is just after the peak of the rainy season and therefore should have relatively high values for green vegetation. Most of the values are high, but there is still a range from 0.4 to 0.59. The fluctuation in rainfall leads to vulnerability of the human economy as

people have planted in anticipation of the rains. As it is the end of the dry season, when evapotranspiration is high and there is Iittle or no stored soil moisture, this time of year is especially critical for the Batemi.

2.5.2 Villal:e Chanl:es

As noted eartier, the Batemi villages were traditionally located on the rocky slopes of the escarpments that run along the northside of the valley, near the water sources. When Gray wrote his ethnography, the Batemi were still located in traditional sites as depicted in Figure 2.7, and he noted that specifie sites were apparently chosen for their defensibility (1963, 29). The villages were relocated to flatter areas in the mid-1970s as a result of the Tanzanian villagization program. An altemate or anditional reason given by villagers was that the Batemi no longer needed to worry about defense against the Maasai. Using the available remote sensing materials (Appendix 1), the past and present locations of villages were investigated. Locations of villages were noted on 1958 and 1972 photographs and used in conjunction with topographie maps and field data to digitize village boundaries. Historical references (Gray 1963 and information from residents) provided additional information on changes . • 28 Figure 2.5 NDVI values for 1984 and 1989. The values are given in 36 dccadel periods (for period dates see Table 2.5). The values iIIustrate the inter-year as weil as intra-year variability in green vegetation. • ~8~------~

~1 _...... _...... _... _...... ~184 -+- 1818 ~ Average 1

o ., il' i i i i i i i i 1 l , .....-"'r""I~~...... -y-~r-r-,-.,..-,r--r-r' 1 2 1 461 7 88101112131416181718182021222324262827282830313213341&5 Perlod

Figure 2.6 NDVI values for the first ten days in May for a nine year period (1982 to 1991). There is a great deal of variability in tbis time of year even though il is only a month after the beginning of the wet season .

~ ~ M ~ U U M U ~ ~ • Average per year Figure 2.7 Location of traditional DigoDigo village. Houses were traditionally cIustered on lower slopes of the hills at the north-side of the valley. Most of the • village now extends south onto the valley floar .

• The locations of the villages pre-1975 and post-1975 are shown in Figure 2.8.

The new settlements (Mgero and Mgundu) are also shown. As the population has

grown, there has been an increasing seulement further south on the plain, although

sorne people have also rnoved up into the hills as evident in the two new sub-villages.

The people settling in the plains area will often have at least a srnall piece of land

in an irrigated area in order to grow crops that do require irrigation. Figure 2.8 also

ilIustrates the location of the villages in relation to the streams.

• 30 • • •

Figure 2.8 Location of the Batemi villages. The original and present locations are indicated along with the newer villages. Note the location of the villages in relation to the rivers and streams. f )J ( [!;:~}, l~//\/r:'\U (/(\ {/ ( \~~L. -/.'\'(f ) 1...-/ -- , , /) L"} \~l' 11/ /. / fT-.J',- ~ 1 ." r- ~;:;;:;,;;;;:- ,~' 1 l' , ...... " "/~~\JIr ' ...... --..' ,~~ ~/ ," '" \ \ , è~~~~~'~----, IJ;- , ~ ) ') ',V- ~ r <:-::::.<=-",:\)\~<:- <;-' b ,~:,~~f~::::-~~'~f~" ) '---~,.,,,--/.4. L'}~~3 \ r~..r-~~j \ 'Tfrf'//z -.J i\"" \'" / 0 ,-' 4.// ('---.S'~\';;l'::::::~~1 ) ~ ~Î~~ ~ljJ\\') ,-2iiC'~"3// 1 /",\~i!J/~<)}/' 2)// J...--' l' \ 2 "---' yi ) \ j v~/l- ;::::.,.r/___ _ :-dj/"-- \/" ,/~'// / ;// ç' ~___ .//-' ,/ " ~~, "\7:. . i'\.)j /"". ~5 J \ ( , ,---;:);/;//: /1r/ ''-1" ~~_.//,/~./~ B" 7~' / // / ~ ./ /k/ 1( ,,'~ _____ " ,. ~/'//-/;::/ phi'/ r / //f:- , '1 '/' / ,/----.." --' ;:;,~/ ~~'-JI! 7 ,- . ___// (~"1 ..,....-/ (~--.. .:><- ''( /V 1" ;,/ ~\-/-J;'j ~.// /---""'> / /7; ( / / ' / ' --..,~, \ \ ./ / r·· 1 1 ,./ /, l' IX 1// / / / (?,l ,/,.- /f l' " ~_ 'l', v /r_' ,/ 1 \ " 1 l/J;=-:-" / " ".1(( -" \ (( )4-~\'(YVf' /1r.~~sr;l V (1>\ ~J /1 / ( \~J fi -'':V l"~,,::;'-..~:V_--:;J-'>..\ ~1/ ) r, ~j~ AI)/-1 )-' ,; ~'J \ , ~ /./'---' \\ \~)'\ /~ .' -" -'. 1 ./ c-" / dG \ ') Il If") l / r',--\' \( fi ,,~\-- -':-= ..-J/ _./~1" -,j~, \ \\~'),-----Jr~ 6\.11----c.'=:>J- ( ~ ' ({'--\' (;'1'î 1/\"'1 ~\) - (".j r "'l '\ (--' 1 F""\"~-:-_~-- , , l, ,'') '0 \ 1 \ " ' l '. l ,- ~--v- ,1 .../ / /1\ :ï.> \. r-'-~,,:.../ \'( \\'l", ) " , -c 5/-"~-)J )" -/ '\ ~ -) -- . 1.' ('" ___ \\\ \.,t /, 1,,' 1 _---1 ...... / r')1 j' ~ \ -- ' / ' ,,/., ('- ----,~)..--' ",-, , 1 - / /// 7' ,,'.,J / -/ \ / -- 1 . :' _ / (J~ ~'I( ,~ f 1 1 • Scale 1:75,000 0 1 ---.l5 KM Wynel Smith 1993 Legcna: ---- Location oh'iUages pnar ta 1974 ---- - Ele\auan 1 - Samunge 4 - Kisangrro 7 - Mgundu 2 - DigoDigo 5 - Gmernment and schools 8 - Mgero - Locauon of villages after 197~ -- -- - Streams 3- Mugholo 6 - Eyasi • 2.5.3 Chanees in Land Cover Determination of the extent of change in woody vegetation cover over the last thirty years was based on the analysis of the aerial photographs from 1958 and 1972, satellite information for 1990 and 1991, and recent field observations. The 1972 air photo was scanned and transferred into the GRASS GIS system. Major areas of change were noted and manually digitized using the 1972 scanned aerial photograph

as the base. Areas were classified as being deforested between 1958 and 1972 or

post-1972. The area totals were calculated by GRASS. Error was estimated by

obtaining areas from a manual calcula tian using a dot-grid technique. Between 1958 and 1972, 1.09 km2 or 109 hectares in forest area along the escarpment were lost and another 0.27 km2 or 27 hectares2 were cleared after 1972,

probably in 1974n5 with the movement of the villages and for agricultural plots.

Figure 29 depicts the areas of major bush clearing. The areas calculated are based on easily identified deforested sections of the valley and do not identify areas of spot

cutting. At present, there are a number of small areas along the northem escarpments that are being marked for clearing for agricultural plots. The overlay of the present village locations indicates that at least sorne of the larger deforested areas are due to the relocation of villages.

Besides these areas of major forest or bush clearing, there has also been

cutting of trees on the valley tloor. Local villagers described the necessity of villagers

2 According to the dot method, 1.28 km2 was eut prior to 1972 and 0.35 kml after 1972 So the computer method actually underestimates the extent of the area deforested . • 32 moving further out into the plain as a result of population growth. Despite the slope • gradient of 1-3% in this area, severe erosion is taking place due tn agriculture and increased grazing pressures by goats and sheep. Figure 2.10 illustrates the type 01

erosion that is common on the valley tlom.

Figure 2.9 Cleared forest areas in the Batemi valley. The areas illustrated only indicate areas of major bush clearance. This does not outline areas of moderate woody vegetation cover that have been subject ta cutting. r------

L-______5KM_

Wynet Smith 1993

- Elevation • Areas c1eared between 1958 and 1972 - Rivers o .Areas c1eared after 1972 - Villages

• 33 Figure 2.10 Erosion on the flat land of the plains is quite common in sorne areas of the valley. Possible causes are overgrazing and consequent decline in vegetation • cover.

.- -... ~. .~ ..... • ... .. '!4j. •.

• 2.6 Conclusion Within the Batemi valley, sorne fairly major changes have taken place during the last 25 years: social, cultural, political, and environmental. It is important to

consider all of these factors III resource management and conservation planning. The areas that change fastest are most urgent from a conservation stand point, but tbey may also he richest areas (which is why they attract action). In the next chapter, the Batemi use of "natural" woody vegetation is examined.

• 34 • Ompter 3. Use of Woody Plants 3.1 Introduction Woody vegetation is an important economic, social and cultural resourcc in many rural societies. Individual species may serve special needs and sorne species may he highly valued. Traditional husbandry or conservation pmctices may be imbedded in the culture and will be sensitive to local resource needs. As planning and resource management discussions are centralized (or become the responsibility of centralized agencies) it is important to be aware of the detail of the interaction between natural and social systems. Knowledge of key resource specics und of traditional conservation practices can be valuable additions to sustainable development and conservation planning. ln Gray's (1963) ethnographie study of the Batemi, he mentions a number of types of use of wild plants, including material for houses, village gates, fenees, firewood, digging sticks, food and medicinal uses. Batemi reliance and potential impact on natural vegetation continue today. This chapter presents more detailed findings on Batemi use of woody vegetation. Ethnobotanists colle ct data on traditional or indigenous use of "wild" plants. Standard categories of data coUected include: fuelwood, construction, household implements, fibres, food, medicine and rituals (for examples, see Boom 1989 and Prance et al. 1987). Data are usually collected and then classified into these categories or ones based on indigenous use. Ethnobotanical work has been traditionally very qualitative, with data coUected in a casual, non-quantitative manner. Studies rarely outline methods used to colle ct and cite data (Johns et al. 1990). More recently, studies have been attempting to quantify the importance of medicinal plants • 35 (Johns et al. 1990) and to quantify the percentage of available species that indigenous • groups use (for examples see Boom 1989 and Prance et al. 1987). Other studies attempt to quantify use-values (Prance et al. 1987; Vasquez and Gentry 1989). In mast studies, data are callected either through an interview-artifact

technique or, more recently, an inventory procedure (Boom 1989; Joint Forest Management 1992a and 1992b). The former method involves asking names ofspecies

used for specifie purposes; the latter involves inventorying a section of forest,

frequently a hectare, and then inquiring about the uses of each species. The interview-artifact method is the standard ethnobotanical approach. The second approach has been used more in recent years in studies undertaking to quantify use

of species and the extent of traditional or local knowledge that may have applications

in conservation (see Boom 1989; Peters et al. 1989; Prance et al. 1987). White a

combination of these methods would he desirable, time constraints made that impractical in this case and oniy the former was used.

3.2 Data Collection

Data on non-medicinal use of woody vegetation -- construction, implements, fuelwood and services -- were collected during two visits to the Batemi area The

data were collected during informai interviews with groups from six different locations (the villè!ges of DigoDigo, Mugholo, Samunge, Kisangiro, Oldonyosambu and the Samunge sub-village of Mditu) (see Table 3.1 and Figure 2.8). These informai groups were made up of people who were in the central village areas during interviews being

conducted by Johns et al. (n.d.a, n.d.b). With one exception, the interview groups

were aU male, ranging in age from about 14 to 65. The problem of access to women

is worthy of comment. While it is true that women are quite knowledgeable about

• 36 Table 3.1 Description of Interview groups . • Village Interview Group DigoDigo six males Kisangiro seven males, various ages Samunge five males Mugholo nine males Oldonyosambu eight males Mditu three young males others - young women or girls

the environrnent and do a iarge percentage of the work, they tend not to he forward in dealing with outsiders. 1 had hoped that my heing fernale would make access

easier but because 1 was required to work through a translator, ~lOd the vast majority of educated youth are male, it was still difficult to interview womell. Additional information was gathered by further individual or group; nterviews and by the author's observations in the field during the biological survey in August.

Sorne of the conversations in the field were with fernales, such as when 1 encountered women or girls collecting firewood. The interviews were conducted by the author with interpretation by Tom Kimanani in June and July 1992 and Frederick Sedia in August 1992. The artifact/interview technique discussed above was used.

Data on four categorie:; of use were collected: firewood, construction, household implements, and services. Groups were asked to name spccies used fll! specific abjects within these non-medicinal use categories. Respondents were asked ta name species used for the following construction mate rials: house poles and doors, beehives, village gates, hyaena traps, fenees, furoiture and rope. Queries were made conceming various implement objects such as walking sticks, bows and arrows, cooking utensils, digging sticks and handles for hoes. Serviee uses discussed

• 37 included live uses of woody vegetation, such as fences or boundaries and shade . • Interview groups were also asked to identify the preferred or most valued species for a given use, if there was one, or if there were many species that could

he used for a give n purpose. The analysis involved tabulating ail reported uses within a use category and listing ail species named. Multi-purpose species were identified. These are defined as those species used in two or more general use categories. For these purposes, the food and medicinal data collected by Johns et al. (n.d.a, n.d.b) are included. Species that are particularly valued for one specifie use are termed single-use species. Indirect uses such as animal food and ecological value (that is, keystone species of environmental significance) were not pursued. Data on food and medicinal use were not coUected as these were Leing studied by Johnr. et al. (n.d.a, n.d.b). References to the religious significance of specifie species used by the

Batemi were noted but this information is Jess systematic and is discussed only in Chapter 5. Additional data coUected in the interviews, including peoples' comments

about species that are perceived ta he declining or harder ta find and where rare

species can he found are included in Chapter 5 under the broader category of

"traditionaJ" knowJedge.

3.3 Reluits A total of 102 woody species, representing at least 58 genera (6 species are still unidentified) and 37 families, are used by the Batemi (Table 3.2). Many of these are muJtipJe-purpose species .

• 38 • •

Table 3.2 List of woody species used by the Batemi. Multi-purpose species numbers indicate number of general uses. The numbers in the next four categories (construction or building materlals, implements, fuelwood and services) indicate the number of times the species was cited as being used for sorne purpose within each given category. Under medicine and food, the numbers indicate individual citations of use (data from Johns et al. n.da, n.db). IFamilV ISpecies Ivemacular Multi ouila Im~. j"uel service Maalc. Fooa Amaranthaceae Sericomopsis hildebranc:Jtii nalubaru, nambaru 1 3 Anacardaceae Lannea schimperi kijombeta 1 2 Lanneasp. mtoregani 1 2 Lannea schimperi mginkinywa 1 3 3 Lannea stuhlmannii msarya 1 2 Ozoroa mucranata mgalati 2 6 7 Rhus natalensis busigiyo 1 2 Annonaceae Uvaria schlefferi msilimbu 1 1 3 Apocynaceae Acokanthers oppositifolia msongo 1 Carisse edulis lumeme/mbaghao 2 9 2 Asclepiadaceae Sercostemma vimine/e minyore/mbebe 1 2 Asteraceae Vernonia amygda/ina mtembereg'1u 2 1 3 Balanitaceae Balsnttes segy,xics mjuiya 2 1 5 Boraginaceae Cordia atricana mringaringa 2 6 1 Cordiesp. mgombeha 3 6 1 1 1 1 Cordia gharaf muhabusu/ngereh 2 1 1 Cordia quarensis ng'on9'o 1 1 Cordlssp. mto 2 2 1 Burseraceae Commiphora mrieana kidirigheta 1 2 Commiphora ellembekii mwaraheta 1 5 Commlphora madaganscensls msisiyo 1 2 Commiphora pelleifolis muluba 2 5 3 Commiphors schimpen msilale/mrunye 1 1 Comm/phors sp. mrumye 1 Caesalpiniaceae TamsTlndus indica nsisi 1 6 Canellaceae Warburgls sa/utarls msega 1 14 Capparaceae Bosc/a sngustifolts munyagu 1 2 1 Boseis consees jugumetu 1 3 Cspparis sp. mrera 4 1 1 MaeruasD. kasingiso 1 -- 2 1 • •

lt'amilV Ivemacular MUfti Build ImDlem. l"ueI Meerle. Food 1'WUI"Uleteceee 1COtnlNetum molle mtewamgongo ~ 1 .,- CombreIumpedo/deI rnkong'onI 1 1 Combtetum .p. msaghu 1 Ebenacl.I EucINIIICemosa rnasegenetu 4 3 1 4 4 Euphorblaceae ktIlypha voIlcensJl munyurt 1 1 Bridel/a mlcremtre bara 1 3 Croton dlctygemous mgllalugVrnslnl 4 1 3 1 6 Croton megeJOCtIIpus ekltalambu 2 1 11 Euphorbla candelebrum klroha 1 1 Euphorbla cuneatrJ Iddingo ka ''l:I'''' 'li" 1 1 EuphOrblatirucalll kldlgho 2 1 1 JltrOpha curcus mgulungulu 2 1 2 Rle/nus commun/. mubono 1 1 Guttlferea Gercenl. IlvIngstonei mblgo 1 7 UIIaceae Noe.p. klhandl 1 1 Noe,p. elambola 2 1 1 Aloe,p. eIongo 1 Loganlceee Strychnos hennlngsll klbunJa 4 3 4 1 8 M.tvaceae HIbiscus caJyphyllus klraraha 1 1 MaIlaceae Tr/chflla emerfca mdaghamlra 2 1 2 Turrearobuste mnyama 1 MImoeaceae Acacia brfNI,pIca mhentkl 1 1 lIcacIa go«zJ msIgIslgl 3 2 1 4 AcacIa men".,. mng'orora 4 10 2 3 12 Iœcla nliotica klJeml 4 6 2 13 2 Acacia nubIca oIdebe 1 9 1 k:ac/a robusta mzlronl 1 k:ac/a Jt8trthoplrloea mrera 2 2 3 kac/a ton/II, mkamahe 3 5 4 4 kac/a senega/ mhutl 2 1 7 NblzII antheImIntica mrl"'mukutanl 2 1 10 DlehrosttlChayac/nerea k/holl 1 4 Moraceae ficus ,ycomorus makoyo 3 7 1 7 Flcussp. mtoyo 1 3 Ficus glumosa mubugl 2 2 Ficus DoDUi"oIla a 1 3 1 • •

Ir.... lly IVenMlCUl. MUftI l'Ulla ImPlem Fuel _...... MecliC. FOOG I.. ·ame••• I,.,cuaep. rnsaganota 1 Flcua wtIkfIIIeIdIl ndera 1 5 MyrsIneceee MyrsIneIIIt1œne nghasI 1 14 lnilCaClIllI Xlmen/a œ/fra mlorna 2 4 8 ... ..,...... - NxUI pteCfIlOrIus rnnyete 1 1 OrmocarpumePo ekurehe 1 1 OrmocarpumIdrldl mJemanJagu 1 9 Phytolaclcell PhyIoItICCttdodecandra mhaka 1 4 Plumbego zeylenica lughlrl 1 PIurn"'""W"-- Rublaceae CanthlumIf1tIflorum mgogora 1 4 Hymenodlctyon pervlfolium klrfghogho 1 Venguerla apieultlla mgholoma 2 1 3 Rutaceae C/eusen/ean/_ mnyoka 1 1 Tee/. a/mpllfolle mwararI 1 1 Zanthoxylum chelybeum mulongo 3 3 1 1 SaIvadorIceae SaIvador8peflica msago 2 2 15 Seplndacele Heplocoelum loi/ooaum eglrlglrya 2 5 2 Pappea ca,..,.,. klboboyo 3 1 12 2 Sapotaceae Mimusopakummel ghlnana 3 7 1 1 51mbarubaceaeHarrisonia abyuln/ca toro 1 25 9atan1CeH SolanumInca:,um mdaghu 1 2 Solanumaetaceum mghamla marlba 2 4 1 WIthtlnI8aomnlf.,. mJonl 1 8tercu1llceee Dombeya umbrIcuIIf",. gwaretu 2 2 2 Sterculie quenqulobla mgURIrnetu 1 3 tnuaceae Grewia blcoIor ebushenl 2 4 8 GrtIWIe trIchocarpa .... 2 2 1 GrtIWIe vfnoaa meabMabwa 1 2 .... Cterodendrum myricoldes mgutugutu/mhura 1 6 1"--- Clefodendrum rotundlfollum kqubl 1 1 esughubetu 1 1 kI)erwe 1 2 kltlO 1 2 lorIeni 1 1 madasha 1 1 mduballoldubal 1 4 - * The last six species have not been identified. ~.3.2 Fuelwood • Use of wood for fuel is probably the most intensi~e and ecologically-significant use of trees and shrubs in the area. Wood is the main source of fuel and lighting in the valley. Most people burn wood directIy; a few people in Samunge make charcoal and this is sold in Loliondo. There are very few individuals who have kerosene lamps. Firewood is collected in a number of ways: ranging from the gathering of dead branches and trunks to felling of trees or cutting of branches. In general, respondents indirated a tendency or willingness ta utilize any available species for firewfiod. A number of specifie species were mentioned, however, for a total of 23 sJk'cies (Table 3.3). The species mentioned most

Table 3.3 Species citcd as used for firewood. This list 1S by no means exhaustive.

o.source Acacia brevispica K Acacia goetzi msigisigi S Acacia mellifera mng'orora OKa Acacia ni/otica kigemi KM cia xanthoph/oea mrera KM Acacia tonilis mkamahe KMSo oesp. elambola S oesp. kihandi o anites aegyJXica mjuiya K Capparis sp. mrera a Combretum molle mtewamgongo D Cordiasp. mto D Le~nd: Cordiasp. mgombeha D D = DigoDigo Croton dictygamous mgilaJugi o M = Mugholo uphorbia cande/abrum kiroha D o = Oldonyosambu uphorbia tiruca/li kidigha DM icus sycomorus mkoyo o K = Kisangiro Grewia trichocarpa esere K S = Samunge aplocoe/um folioosum egirigirya Ka Md= Mditu appea capensis kiboboyo D o = other trychnos henningsii kibunja M Tr/chi/ia emetica mdaghamira M Zantho tum chal beum mul 0 a

• 42 frequently include: Acacia tortilis (four villages) and Acacia meJ/ifenl (three villages) . Acacia nilotica, Acacia xanthophloea, Euphorbia tirllcalli and Haplococlunl fcJ!io"sulll

• 3':"C were all mentioned in two villages. There are also a few species of plants that used for specifie purposes. Aloe species (kihandi and elambola) are lIsed spccifically for smoking bees out of beehives when it is lime to colleet the honey. Specics

mentioned as most preferred or more highly-valued species were the ACilCÙI spccics (A mellifera, A tortilis and il nilotica).

3.3.2 Construction Materials Construction materials are another major use of wood in the Batemi arca. A total of 39 species were mentioned as being used for construction pllrposes, ranging from bouse materials, ta fenees and beehives (Table 3.4). Building of houses is one of the main construction uses for wood. A traditional house is constructed entirely from indigenous plants (Figure 3.1). Large poles (usually an Acacia species, Haplocoelum folioosum, Ozoroa mUCféWéJta or Mimusops kummel) are interlaced with smaUer poles from a Cordia specics (mgombeha) or Strychnos henningsii. Further south on the plain near Sale, Cordia gharaf, or muhabusu, is used. The roof poles are preferably Dombeya umbraculifera or Strychnos henningsii Rope, from various trees such as Sterculia africana or Uvaria schlefferi, or reed species such as Cyperus alternifolius, is used tn tie the pales together. Various grasses or reeds are then used for thatching the roof. The actual doors are single planks hewed from the roots of large trees. Ficus sycomorus is the most commonly used species, as its roots nre wide and sprawling. The Batemi leave the majority of the tree intact, cutting out only a section of the root. The other tree commonly used for doors is a Capparis species known as rnrera .

• 43 • Table 3.4 List of species used for construction. Given by type of use and place of citation. The category columns are: building poles, beehives, village gates, hyaena traps, house doors, rape, furniture and fences ..

SpecIee v...... Polle Beehive Gates r,.,. Door R®e Fum. FInCII ~Ia senega/ mhUII 0 ~/Bgoetzl msiglslgi S Md 4cacla melli/era mng'orora DKMSMdO K KS 0 4cac1a nllotica kljeml MS K KS 0 4cac1a tort,II, mluunahe So K K 0 Nb/zia anthelm/nt/ca mm 0 gelanltes aegy~/ca mjuiya 0 90Icia angu,tifoliB munyagu 0 0 Srldella mlcrantha bara 0 0,0 o.pperls sp. mrera c Pombretum pedoldes mkong'ongI 0 Pombretum mol/e mtewamgoIlgO 0 Pommlphora alrlcBna kldlrlghela 0,0 Pomm/phora ellembekli mwanheta 0 KMSMdO Pommlphora pel/ifolla mulube 0 KSMdO 0 Pordla afrlcana mringMnga 0 DMMdS,20 Pontlasp. mgombeha OMS pordla gharaf muhaibuIu 0 Proton dletygamous mgillllugl 0 broton megaloc8rpus ekltalambu 0 pombeya umbraculifera gwInIu 00 D/chrostaehays cinarea kiholl MSo 0 r:uclea raeemosa mragenetu KSo leu. syeomorus mkoyo MSMeI MSM rJrewla bleo/or ebuIhenI KSOo ,"",ocOfJ/um lolloosum egiriglrya DKMOoo t.enneBsp. mtoregenI SMei "'/muso". kummel gMnana DKMo SMdO pzoroa mucfBlllJta mgIIIatI MSMd SMdO ~.,.culla quenqulobla mugurumeIu 0 00 ~hnoa hennlngsll kibu;a M !rea/ea .Impllfol/a mwarwI 0 ~ .chlefferl m8IIimbu 0 Vanguerla apleu/ata mgholoma 0 Vemon/a amygdalina mtembereghu o. Zanthoxylum cha/ybeum mulongo 0 0 0 esughubelu S kijerwe SMd k'* 00

I..elCodj D = DigoDigo K = Kisaogiro M = Mugholo S = Samunge o = Oldonyosambu Md= Md.itu • o = other Figure 3.1 A traditional Batemi house is round and constructed entirely from local • mate rials.

•

Sorne of the newer houses use wood only for the house frames, while mud is used ta plaster it. The wood is frequently a cedar bought from the Loliondo arca.

The most recent type of house structure is made from local bricks. This type of construction seems ta be restricted to young people who have jobs and therefore the money to afford such a house as their are labour costs for building bricks and the roof is usually made from tin. The largest portion of houses, however, arc still constructed in the traditional style. Furniture and platforms inside the houses are also constructed from wood. Combretum padoides is used ta construct the platforms installed in the houses to • 45 hold grains and beans. Vernonia amygdalina is used fnr bedframes. Wood is also the main material used to construct fenees, beehives, village • gates and animal traps. Particular species are preferred for many of these uses. Fenees are mostly constructed from acacia species, such as Acacia mellifera, Acacia

nilotica 01 Acacia tortiJis, along with Balanites aegyptica and a few Commiphora

species. Respondents indicated that branches of acacia trees are preferred for fenees around houses and gardens (or shambas) as their thorns make them suitable for barriers. Zanthoxylum chalybeum and Vangueria apiculata were also mentioned as

fcnee species.

Beehives are an important part of the Batemi culture, with most men ha ving

beehives (Gray 1963). They are constructed from hollowed out logs, derived mostly

from hardwood species. The beehives are plaeed in the forks of trees, surrounded by poles to hold them in place (Figure 3.2). A total of 18 species were mentioned as used for beehives. According ta respondents, the most sought after tree trunk for

beehives is Cordia africana (mringaringa), which was mentioned in 4 villages. The

use of Cordia africana for beehives is quite restricted as they are mainly only found

along irrigation channels, where cutting is prohibited except ta the Wenamije or elite.

As this species is not widely available, a few other species are substituted, incIuding Commiphora ellembekii (mentioned in 5 villages) and Commiphora pelleifolia (mentioned in 4 villages). Other species mentioned include Ficus sycomorus, Mimusops kummel ar,' Ozoroa mucranata.

Village gates and hyaena traps, for which there is no longer any great need,

are made from Acacia species, such as Acacia tortih"s, Acacia nUotica and Acacia

meJ/ifera. These species are considered to he the most desirable for these uses.

• 46 Figure 3.2 Beehives are placed in the forks of trees within bundles of poles. Trees • often contain a number of beehives.

•

3.3.2 Household Implements Implements are generally made from shrubs or smaller trees. A total of seventeen species were mentioned during the course of the interviews and a few of

these are used for more than one type of implement or tool (Table 3.5). The types of uses include walking sticks, bows and arrows, digging tools, spoons, and toothbrushes. Grewia bie%r, Acacia me//ifera, a Cordia sp. (mto) and Grewiu

trichocarpa are ail used for walking sticks, with the first species being the preferred one. • 47 Table 3.5 Species used as implements. Listed by place of reference under specifie type of use. The categories are: walking sticks, rungata (authority stick), digging sticks, handles for implements, bows and arrows, toothbrush, and others. • vern. mnyeI8 0 mng'orora SO 2 munyuri S 1 mnyoka 0 1 kijuba 0 1 mto DM 2 mgllelugl M 0 0 3 gwaretu MS 2 msagheneIu 0 ebushenl DKMOo 0 S M 8 eaere Ko 2 klraraha 1 ngulungulu 0 1 mbono 0 0 1 rneago KO 2 ldbunjII DSo D 4 0 1

Le&end: D = DigoDigo K = Kisangiro M = Mugholo S = Samunge o = Oldonyosambu Md= Mditu o = other

Digging sticks, an important impIe ment in the past, are made from Strychnos henningsii or Croton dictygamous, with the former the most preferred. Bows and arrows are made mostly from Dombeya umbraculifera, Acalypha volkcnsij, Buc/ca raccmosa, Grewia bicolor and Ricinus communis. Other types of uses and their species include: toothbrushes (Salvadora persica), and hoe handles (Strychnos henningsii and Grewia bieD/or).

3.3.2. Services The Batemi also utilize live trees for a few services, including fences, boundaries and shade. Five species were specifically named (Table 3.6). Jatropha • 48 Table 3.6 List of species used for services . Genus and Species Vernacular Type Source • Boscia angustifolia munyagu shade 0 Euphorbia tirucaJ/i kidigho fenee 0 Jatropha curcus mgulungulu fenee 0 Jatropha curcus mgulungulu boundary 0 Maerua sp. kasingiso shade 0 Mimusops kummel ghanana shade M

Lel:end: D = DigoDigo K = Kisangiro M = Mugholo S = Samunge o = Oldonyosambu Md= Mditu o = other

curcus is used for both live fenees and as boundary markers between fields or along ra (1s. The other species that is highly visible as live fenees is Euphorbia tirucaJ/i, especially in Samunge and Mugholo (Figure 3.3). A Macrua sp. is one of the spccies used for shade in home compounds, as is Mimusops kummel. These species are carefully preserved for shade or planted and managed for purposes such as fenees and boundaries. A few other species were also used as fenee species, including Commiphora madaganscensis.

3.4. Dilcussion The various non-medicinal uses described above are important for the Batemi. Many of the species derive their value from a range of uses while others are only

used for single purposes.

• 49 Figure 3.3 Euphorbia tirucalli functioning as a live fenee. Notice the newer type of • house construction in the background.

;;~~-;.~ . ~;... ~. _ ....::~ .... 1. "' •• .:.2,l,},iII._, ••• ,:;t. u' ,.",,..\,0 :.. •

3.4.1 Multipurllose species

A number of the species can he classed as key multi-purpose species, that is, as trees or shrubs which provide a range of goods or services. Fifteen are used for three or more general purposes, including food and medicine purposes, and forty are

used for two or more (Table 3.7). Many of the most widely-used species, in terms of general use categories, are

Acacia species. Acacia mellifera is probably the most highly-valued amongst the Batemi for its strength and termite-resistant qualities. It is used for Medicine, fuel, building (mentioned in a11 6 villages) and implements. People continually stressed • 50 Table 3.7 List of species used for multi-purposes. The tahle lists number of general uses and then the number of uses within the construction and implement categories, as there are eight and seven sub-uses within those two categories • respectively. Species Vernacular # uses Build lmp Acacia goetzi msigisigi 3 Acacia me/lifera mng'orora 4 4 Acacia ni/otica kijemi 4 4 Acacia tortilis mkamahe 3 4 Capparis sp. mrera 4 Commiphora ellembekii mwaraheta 2 Commiphora pel/eifolia muluba 3 Cordia sp. mgombeha 4 Cordia africana mringaringa 2 Croton dietygamous mgilalugi 4 3 Dombeya umbraculifera gwaretu 3 EucJea racemosa msanganetu 4 Fieus syeomorus mkoyo 3 2 Grewia bie%r ebusheni 3 2 4 Haplocoelum folioosum egirigirya 2 Mimusops kummel ghanana 3 2 Ozoroa mucranata mgalati 2 Pappea eapensis mgurumetu 3 Sterculia quenqu/obia kiboboyo 2 Strychnos henningsii kibunja 4 1 2 Zanthoxylum chalybeum mulongo 3 3

that it was one of the strongest trees and the best for building. Three other acacia

species are also widely used: Acacia tortilis, Acacia nilotiea and Acacia goetzi. Ali

of these are used for fuel, building and medicine. Cordia and Fieus are widely used

genera, with a Cordia sp. (mgombeha) and Ficus sycomorus as two of the species that

fulfil a number of roles. Shrubs that are widely used include Croton dictygamous, Croton mcga/ocarpus,

Grewia bie%r, and Strychnos henningsii Most of these tend to he uscd for

Medicine, fuel, building and implements. A few of them are highly valued for specifie

purposes, including Grewia bie%r, the most prized species for walking sticks . • 51 Sorne species are also widely used within one general category type (such as construction or implements). For example, Acacia me/lifera, Acacia nilotica and • Acacia torti/is are aH used for four types of construction purposes. Within the

irnplement category Grewia bie%r is used for walking sticks, rungatas, handles and bows and arrows while Croton dictygamous is used for walking sticks, digging sticks and bows and arrows. Strychnos henningsiiis used for digging sticks and hoe handles.

3.4.2 Valued. Sinile-Use Species There is also a class of species that, although not multi-purpose, are highly valued owing to their suitability for one specifie purpose. Notable amongst this category in terms of construction rnaterials is Cordia africana, which is the most preferred species for beehives. It was mentioned in five villages as being used for beehives and was referred to as the most valued for this purpose. HaplocoeJum folioosum is another species that is widely used as one particular material, in this case

house poles. Many of the medicinal plants, such as Harrisonia abyssinica, Warburgia

sa/utaris and Myrsine africana are single-use species.

3.4 Conclusion

There are sorne species and families that can he easily designated "key" social or cultural species, ones whose existence is important to the cultural, social and even

economic life of the community. The data in this chapter provide an indication of

the more valued or "key" species to the Batemi. The task of identifying key species is discussed further in Chapter 5. But first, biological data, which is also required for conservation and lesource planning, is presented in Chapter 4 .

• 52 • Chapter 4. Woody Vcgetatior. Distnbution and Abundance 4.1 Introduction The next step in the research was to conduct a quantitatIve study of the structure and composition of vegetation resourccs in the area. Although thcrc have

been rnany vegetation studies conducted in the rcgÎoIl, such as in the Ngorongoro Conservation Area (Herlocker and DlrschI1978), ulke Manyara National Park (Loth and Prins 1986) and the Maasai Mara area in Kenya (Lamprey 19H4), there arc no baseline data available for the Batemi area. This chapter presents and ÙlsclIsses

findings on the woody vegetation, focusing on species composition, abllndancc and

distribution. There are three components to this data. First, there are the basic inventmy and spatial distribution data, which provides a general sense of the abundance of the species found in the area. Second, classification and ordination of these data then provide general vegetation types and an ide a of the habitats of each type. The final compone nt is a landcover map, which was createù from Landsat

Thematic Mapper (TM) digital data. The vegetatio!1 types from the classification and

ordination are depicted on the land cover density classes on the final map.

4.2 Mcthodology

4.2.1 Data Collection 4.2.1.1 Random Samples In DigoDigo Ward, the areas of most intensive use are the valley floor, the hills occurring within the valley and the lower slopes of the escarprnents at the north edge of the valley. These were targeted for study. The limits of the study area • 53 (Figure 4.1) follow the 1imits of DigoDigo ward, except on the northern-side, where

they follow the 1400 meter elevation mark. Random sampling was use d, as

• recommended for ecological and conservation al survey work by Usher (1992). One of the main objectives was to investigate t:le availability of species for ail four of the main villages. Therefore, to ensure coverage of the full area, the valley was divided

into three adjacent, equal sections (Figure 4.1), each to he sampled separately.

The species-area method was used to determine the optimum area for quadrat

size. Five repeated nested quadrats of 25, 100,225 and 400 m2 showed that 10 x 10

m was an appropriate size (Table 4.1), the size also used in similar environments by many researchers (Fuis et al. 1992; Kennenni 1991; Kigomo et al.. 1990; Loth and Prins 1986).

ft was initially determined that 150 quadrats would he sampled but that the

species-area relationship would he monitored and if the number of species were not

approaching an asymptote, the numher would he increased.

Locations of samples were marked on a topographie map from coordinates extracted from a random samples table. Locations falling outside of the area were

Table 4.1 Determination of quadrat size using four sizes of nested quadrats with five replicates.

Size of Quadrat . 5 x 5 m 10 dO m 15 x 15 m 20x20m Ouadrat 1 2 4 4 4 Ouadrat 2 6 8 9 10 Quadrat 3 2 3 4 4 Ouadrat 4 4 7 7 9 Ouadrat 5 4 6 7 7 Mean 3.4 5.6 6.2 6.8 • 54 • • •

Figure 4.1. Design of sampling stmteb'Y. Tht! thrt!e sections of the sam pit! art!a, the randolll 4uadrab, and the Irngation channt!b invt!ntorit!d art! ail shown. 1 - , ! r 1 Ti ; , r, .) - / i (-. ,] r' f • / 1 l ,( ) , 1 { . ", '\ 'Il) \ l ) 1.., 7 1 ) ), ;:: \ '~_l)) "f' _ 1 1 l ' "-'î (f 1 -. 1 1;" 1 ' • / .,"\' \ 1 \ . /' \ _. ~__ _/_._;/ l'~'~'\,::=-/~\-",l.,'~""'-\ L~,r~:~-\ ,'/ () »\'" ),\ n\'\~)__, - --, ,,)\ ,. " '-. 'r~~ l\ j 1 , ~ i." ")1 /' (' \, -, -_'f f' , ~,_.___',.''" 1,. ,,- r ')\,-- ____ ), _ ,_ 1('./, __ / ...... _____ \ ,\ /~" ,d 1 ) ". ' \" _ "' '/'\ " , ,/ 1 l ' , ----- \ - , .r" ) ---- '-.. '" ''\ ..'~/[-- -" ,', \ "I/"~:-',,/(' , " , 1 ~~- . • \ ,~:',-" .' J J:' '--,, \ (.---. '-.., >-JI ~,. )" _---,.\ • ,'/ J / -1 ' 1 1 . - ,." - 1 '-'-,) "\ ," .~-," / l "1 .----, " ' , -' , ' ' - -, _ ,:i.:,- ': -, /;' ,t,,( , 1 ( \ L C ,'-.J :-, ~.>;>/ ,- , \ •• "",~__ ~\y_ ' 'f -- -',.-- • '\'.-. __ , , ",__ • (1 1" " ,"III 1l' ',(,Il \'1 ' ,. _ _ II~' ' ' , J • '1'\ ~/'-'-"'.. "':"J~/'-:..-, _ --, ,_, \ - '"( /' \ _ /-'-\ , \ /. J:---- \, . . \. \ (' .q' .-'. L.", ',-- ~ , -. - " .-.(.'\ - -_\(,' ('- \ r ' -'. --= ' 1 ~,.--., "~r..,Î~)0) ./ }. _ • · {,f-...... ~~~. J 1 I~) 1 , _.}f' 1 \ \ ,-, -~ - l (-,-~' o,F \ /'. "' L/'1 \ ",y--~ ( ,..> - " -', r ~ 1 ~ ,/' "'./ - 1 , 1 • / .~." .' y.' _ 1 ".-~-- - J · , -r \ \ I:"~,'\ • 1)'ï"";- \ • ___ __., •..j ( 1 \ • " \ ____ \ , ( 1 -' '. '. \' "f." • C " r­ ../ ,­ ' .) \ , .--- • l , '. • \ \\\\..::; \\ / _ J .,'> \.\ '1\ ,', . \ .'/_ ., •. , ,l, r / ,/' l"· 1 --- \ ) '" • " • r t \- ' \ 1 l, __- _ - L-_ ~...... )

1" .' .1-- .' ____ L~._t " Sc.llt!: 1:75.000 Wynet Smith )(}

species3, specimens were collected, described, catalogued and later taken to the University of Nairobi Herbarium for identification. For each individual, height class and diameter at breast height (dbh) for trees were recorded.

4.2.1.2 Additional Data A1though random sampling was the principal method used, the se data were supplemented with comprehensive surveys of irrigation channels. These riverine species are distinct and important but have a very low spatial distribution. Complete inventories of four of the principal channels were conducted (Figure 4.1). Additional species information was also collected by noting the presence of species in the village areas and when exploring the more remote escarpment areas. These data are not included in the density and distribution analysis based on quadrats.

3 An initial inventory list of vernacular and botanical names was available due to the ethnobotanical work underway by Johns (n.d.a, n.d.b) . • 56 4.2.2 Data Analysis • Densitr and frequency~ of species for the whole area were calculated. The data from the three subsections of the valley were analyzed altogether. These da tu provide an overall estimate of the availability of the different species. Classification and ordination of the data were performed to obtain a simplified data structure and to detect patterns of variation (Gauch 1982; cf. Kennenni 1991). Classification was undertaken using the hierarchical two-way indicator species analysis program TWINSPAN (Hill 1979), a polythetic, divisive technique that breaks a sample set down into sm aller, associated groups of samples and species. TWINSP AN first constructs a classification of samples and then uses this classification to obtain

a classification of species based on ecological preference (Hill 1979). Bredenkamp

et al (1991 cited in Fuis et al. 1992) found TWINSP AN gave a first good approximation of vegetation communities. The data were ordinated using the detrended correspondence analysis (DCA) option in the computer program

CANOCO (ter Braak 1988). The main clusters of the TWINSPAN analysis are compared with the DCA ordination. Species occurring in less than four percent of the sampling sites were eliminated for the classification and ordination analysis. The final results are based on the default variables in the programs, which were found to provide adequate

4 Density is defined as the number of individuals per unit area (Kershaw and Looney 1985). This measure was chosen as it allows comparison of different areas and different species and is an absolute measure of the abundance of plants.

S Frequency is defined as the proportion or percentage of quadrats containing a species (Goldsmith 1991; Gauch 1982). Frequency is not an absolute measure as values are dependent on quadrat size, plant size and spatial distribution (Kershaw and Looney 1985). • 57 • exploration of the data set. 4.2.3 Landcover Map Classification An attempt was made to produce a general landcover map for the area using Landsat Thematic Mapper (TM) digital data. The classes depicted are based on the percentage of woody vegetation in arder to provide baseline data for resource management and conservation planning. These types of discrete communities are valuable in the process of mapping areas, assessing value for conservation and in determining plans for management, even if nature does not contain such distinct entities (Cox and Moore 1993). In areas like the Batemi valley, there are many barriers to classifying land cover including heterogeneity of cover and topography. One possibly important problem in classification of vegetation or soils in semi-arid areas is mixed pixels, which are pixels containing a mixture of surface cover classes (Schowengerdt 1983,

141). As weIl, there can he variation in spectral characteristics within classes due to factors such as plant health and age. Terrain slope and aspect can also affect spectral reflectance of landcover; the same surface cover can have a wide spectral variation due tCl slope, aspect and solar inclination and élZ'muth (Ahman et al. 1992; Holbein and Justice 1980 in Civco 1989; Schowengerdt 1984, 139). These factors

need to he considered in classification accuracy.

4.2.3.1 Materials and Methods The materials and procedures used to produce the landcover map are iIIustrated in Figure 4.2.

• 58 Figure 4.2. Flow chart of procedures followed during course of production of • Landcover Map.

Landsat TM 1 1 Jo Window ,1, Image Pre-processing

Georeferencing Topographies Maps

'11 Digital Unsupervised Elevation Model Classification

~ " [Reclass Il l Training sites ~

.. ~ Supervised Classification ! statistical Analysis

! Accuraey output Il ... Assessment JI • i) Materials • A range of data were used to investigate and c1assify the vegetation coyer. A Landsat Thematic Mapper (TM) image of Mareh 1, 1991 (scene 169/61) was used for digital analysis. A Landsat TM print (1:100000 seale) for March 1989, aerial photographs for 1958 and 1972, 1:50,000 topographie map sheets (27/1 and 27/2), and field observations were used to aid in the classification process (for a complete list of materials and sources see Appendix 1). The Landsat digital data was an extract

from scene DI69-061, 1 March 1991.

ii) Pre-processin" and imaKe enhancement A subscene covering DigoDigo Ward (columns 4660-5299 and rows 5360-5839) was extracted from the Landsat image. Initial processing of the digital data included

visual and statistical investigation of the separate bands (only 2 and 4-7 were available ). Based on the visual interpretability and screening for redundancy in data between the available bands, 2, 4 and 7 were used for the final classification process. The correlation matrix (Table 4.2) shows the high redundancy between a

number of the bands. Bands 4 and 7 had one of lowest at 0.4207 and band 2 was chosen to complement these two.

Table 4.2 Correlation matrix for four bands available for the Batemi area. Band Range Mean Stand. dey. 2 23-49 34.03 4.07 4 11-131 60.28 7.03 5 25-255 93.38 21.90 7 11-255 49.22 16.17

• 60 m) Geo-referencin.: • The satellite image was geo-referenced to Universal Transverse Mercator (UTM) coordinates using the rectification process in GRASS. Twelve points on the image were referenced and used to rectify the entire image. The root-mean-square­

error (RMSE), usually used to indicate locationa~ error was 27.39 01, an acceptable error given the resolution cell size of 30 meters.

iv) Classification Initial unsupervised classifications were conducted using IDRISI at the Serengeti Research Institute in the Serengeti National Park. The resultant c1usters were investigated with initial field data and aerial photographs and then investigated with further ground truthing. ln Canada, further classification was undertaken on GRASS 4.0 in the McGiII University, Department of Geography GIS lab. Unsupervised classification was conducted on a combination of bands 2-4-7, with various numbers of c1usters. The influence of topography on the classifications carried out was investigated using a digital elevation model (DEM), derived from digitized topographie maps. This was used to visually interpret effects and to help choose the final classes. A supervised classification was then undertaken, with training sites (Table 4.1) based on areas of vegetation that were known from initial ground-truthing, aerial photograph interpretation, and pixel clusters identified in the unsupcrvised classification.

• 61 Table 4.3 Training site statistics used for maximum likelihood supervised classification of the Batemi study area. • Mean, standard deviation and minimum and maximum spectral values for each of the three bands.

Class Band 2 Band 4 Band 7 Bushl 25.2+1-1.5; 23-28 46.5+1-3.8; 38-57 16.6+/-2.2; 11-19 Thicket Woodland 38.5+/-1.75; 34-42 60.7+1-3.3; 53-69 75+1-5.8; 58-90 Wooded 34.8+/-1.46; 32-38 54.1 +/-3.2; 48-61 67.1+/-3.1; 57-75 grassland Grassland 45.3+1-2.63; 41-49 74.9+/-4.2; 68-78 83.1 + 1-4.7; 69-96

v) Errar Assessment

There are many points at which error can he introduced into the production of a landcover thematic map. Table 4.4lists the types of error that a user must he aware of in interpreting the reliability of the final map product. The final map is affected by ail of the factors.

Table 4.4 Sources of error in the Image Processing and GIS process (derived from Lunetta et al.. 1991). Stage Specifie error Data Processing Geometrie rectification Data Analysis Quantitative analysis Classification system Data generalization Oata Conversion Vector to raster Final Product Spatial error Thematic error • 62 4.3 Reluits and Discussions 4.3.1 Species Composition and Abundance • In a1l, there were 101 woody species recorded, representing 54 genera and 37

families (Tables 4.5, 4.7 and 4.9). In the 150 random quadrats (Table 4.5), 1208

individual trees and shrubs were counted, representing 74 species (trees, shrubs and a few woody aloes) of 49 genera and 33 families. The four irrigation channels contained 22 species of trees and shrubs in 18 genera and 15 families (Table 4.7). Another 15 species were seen in the area but did not fall within cither the randol1l

sampling or irrigation channels (Table 4.9). These trees and shrubs represented 13 genera and Il families.

4.3.2 Random Sites Data The species-area curve (Figure 4.3) suggests that 150 samples was adequate.

At 63 quadrats, 64 species had been identified. The number rose only to 74 by 150. Thus, 150 10 x 10 m quadrats (1.5 hectares) were sampled. The most abundant species in the area are Croton dictyga mous (l68/hectare ),

Acacia tortiJis (73/ha.), Vangueria apicuJata (58/ha.), Euphorbia tirucalli (48/ha.) and

Grewia bicoJor(45/ha). Individually, these represent, respectively, 20.9%,9%,6.95%,

5.9% and 5.5%, or, together, almost 50% of the total number of trees and shrubs

found in the sam pie set.

Nine species have densities greater than 20 individuals per hectare (Figure 4.4)

and account for 767 or 63.5% of the trees aud shrubs counted. Eighteen species

have densities greater than 10/ha and account for 954 or 79% of the total trees and

shrubs. Most of the other species occur only infrequently and often onty in restricted • 63 Table 4.5 Random sampling species data.

fMIIIV &Mn "fAlq. , Lannes kIjombeta 8 5.33 2.86 • Lannea mtoreganl 4 2.67 2.86 Lannea s/uhlmanmi msarya 14 9.33 7.86 OzorOd mucrana/a mgaIati 1 0.67 071 ro·""'- Uvafla schfefferi msilimbu 1 067 0.71 ~naceae Acokan/hera oppositifofia meongo 32 21.33 3.57 Safcostemma vlmlna/a mlnyore 9 6 2.14 ~Itaceee Balanites aegypfica rnjuIyu 28 18.67 14.29 Bcnginaceae Cordia afrlcana mrlngaringa 1 0.67 0.71 Cordiasp. mgombeha 4 2.67 2.86 Cordia ghara muhabutu 2 1.33 1.43 Cordiasp. mie) 1 0.67 0.71 Commlphora afrlcana kldltigheta 23 15.33 7.14 Commlphora _flambekli mwMIheta 7 4.67 4.29 Commlphora merle_II kIdIgho ka mg 1 0.67 0.71 Commlphora peflalfofia muluba 24 16 8.57 Commlphora .chlmperl msilale/mrunye 5 3.33 1.43 Senna dldymobotrya eeneIOI 3 2 1.43 T8tn8I'indus indica neIsI 1 0.67 0.71 "". Boscia 81lgustifofia munyagu 12 8 6.43 Capparis .p. mrera 2 1.33 1.43 Maefussp. kaslngiso 5 3.33 3.57 Maerus endl'chll mtrtheje 1 0.67 0.71 Pombreteoeae Combre/um mofla mtewemgongo 5 3.33 1.43 Combretum pedoldes mkong'onl 2 1.33 1.43 Solaneclo mannll ekero 1 0.67 0.71 Iaceee lpames hlldebrandtil abungllya 5 333 0.71 Encepha/a/antos hlldebrandtil esuku 5 3.33 1.43 b: Euc/ea racemosa masaganetu 1 0.67 0.71 ~""'- Aca/ypha vol"ens/l munyurI 58 38.67 7.14 Croton dictygamous mgIIeIugVmaini 253 168.67 22 EuphorlJla cande/abrum kIroha 41 27.33 11.43 Euphorbla .chemari kirlbeji 3 2 0.71 Euphorb/a t/ruca/li kldigho 71 47.33 13.57 Euphorbla sp. kI1eIi 1 0.67 0.71 Rlclnus commun/s mubono 8 5.33 1.43 Garcenla Ilvingstonei mbIgo 2 1.33 1.43 la..__ Aloesp kIhancII 10 6.67 0.71 Al08Sp. elMlboIa 20 13.33 2.43 Strychnos hennlngsll klbunja 17 11.33 2.86 rrlchllla eme/lca mdaghamlra 9 6 4.29 TU"eB robusta mnyema 7 4.67 4.29 ..... Acacia tortifis mkamahe 109 72.67 44.29 Acacia nllotlca kljeml 52 34.67 17.86 Acacia brevlsplca mt,erekl 15 10 8.57 Acacia meflifera mng'OI'Of'a 15 10 6.43 Acacia Jlanthophloea mrera 6 4 2.86 Acacia goetzel melgiligi 4 2.67 2.86 Acacia senegal mhutI 5 3.33 2.14 Alblzla anthelmlnt/ca mrlra 19 12.67 2.14 DIc:Itroatachayt c/nerea kId 1 0.67 0.71 • amity .SPeCIeS l!emacular SUm %Freq. Ficus sycomorus malCoyo 13 IVV'-"-'867 6.43 • maaganoIa 1 067 Ficussp. 071 Ximenia callra mloma 4 267 214 ~Iionaceae Abrus preeatorius mnyete 2 133 1.43 Erythrma abysinniea mng'oring' 1 067 071 Ormocarpum sp ekurehe 6 4 357 Polygonaceae Rumex usambarsis nantororu 1 067 071 Rubiaceae Canthium setiflorum mgogora 5 333 143 Hymenodictyon parvlfolia kirighogho 5 333 214 Vangeuria apiculata mgholoma 84 56 1643 Tec/ea slmpliclfolia mwarari 1 0.67 071 Zanthoxylum ehalybeum mulongo 4 267 2.14 Selvedoraceae Salvedora persica meago 1 067 071 BIipIndeceeIe Haplocoelum fol,oosum eglriglrye 4 267 214 WithBnla somnlfera mjonl 1 067 071 St8rculieceee Dombeya umbracullfera gwaretu 20 1333 2.14 Sterculia quenqulobl8 rngurumetu 14 933 8.57 ..... Grewia ble%r ebushenl 67 4467 17.86 Grew/a similis mnylri meeri 18 12 7.14 Grewia trichocarpa esere 1 067 0.071 .... Obet/ca pinnatifida Klghoghiang'ombe 1 067 071 ~8Ibenaceae C/erodendrum rorundifolium kijuba 16 12 071 C/erodendrum ternatum mhurambura 2 1.33 0.71 TOTAL: 1208

• Figure 4.3 Species-area curve used to determine sam pIe size . • 70~------'------~ 60 .

50 ......

• ...... nu..... •• ...... ••• ...... u ...... u ...... -...... u ......

'0 ~ ~ 30 ...... z

20 ......

10 ......

10 15 20 25 30 35 40 45 55 60 Number of quadrats or samples.

Figure 4.4 Distribution of species density levels .

...... •• ...... 01

...... _ ...... _ ...... • ...... -01

...... " ...... ,...... " ...... - ..

10 20 ~ 40 50 a:J 70 00 00 1'X1 :!XI • Density per hectare habitat:-. Fifty-six species have less than 10 individuals per hectare . • In terms of species numbers, the mast widcly rcprcsentcd familics arc Mimosaceae (represented by 3 genera and 9 species) and Euphorhiaceae (with 4 genera and 7 species). AlI other families are represented hy only one or twogencra.

In terms of abundance, Euphorbiaceae accounts for 435 (36%) of the 120H

individuals counted and Mimosaceae accounts for 226 (1 Ho 7% ). Eighty-nmc individuals (7.4%) of the Rubicaceae family were countcd and 86 individuals (7%)

of the Tiliaceae family.

4.3.2.1 Classification

The hierarchical classification of samples and species obtained t'rom

TWINSPAN analysis shows the main species and sites c1usters identified within the

first four levels of division (Table 4.6). Three vegetation types were informally

named at the third level of division. The first level of division scparated out five

species. The sites can he separated into an equal number of c1usters. The first Icvel

of ~!'!!:;ion separated out 19 samples. The second level divided the remaining

samples into groups of 56 and 60. The separation hetween the variolls groupings are

quite strong. The degree of division amongst groups is often indicated by a high

eigenvalue and the values for the separation at levels 1 and 2 are 0.732 and 0.711

respectively.

4.3.2.2 Description of Veietation types and habitat

From the structured TWINSP AN table (Table 4.6), three main vegetation

• 67 • •

Table 4.6 The ordered TWINSPAN table of sites and species. Numbers are transformed density classes. The top margin gives quadrat (printed vertically) grouped into three main clusters. The bottom and right-hand margins show the hierarchical classification of quadrats and woody species respectively, for 4 levels division. snn AllO SITE GaOJPS Orouplll Group nit Group'" 0rcMIp , Il III """,,, "" Il 1 '",11 III 1 1 Il 1 Il 2883706,992661,246,585,2,344560,,243134903424600",',', 79000296Z 4551!99902 3812179069242333335333213112'583333 22 156828227845185 1946307723950649634461051380141616J7196aS3504298901245641001416124346896924526125285028658 7259034692128?3401SS355719 0187551532392413097 An •• ••• ••••••• ••••••• • •••• 1••• ·.·.·,'"22222222'1222331,, •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• ··········1····---- 000 Ee --·-·---·'2232321113·--····---·--·-·-·-·-··············· ········-·21-·-··-··2·1-1···-·--·· ••• -.-••••• -•••• -••••• -••• --••••••••• -•••• -.- 0010 At ,···1,121·1',12122,122··22221222121,1, ·221 ·121'22322·-23 ••••••• , "'2' ····1 ·-3-1"2--1--"- -1· -, 1- ••• ---. -1·-···1-··· .- ••• ···1··--·--· -. 0011 Type 3 A4 ----·····-·-·······2···3··-·-··-·3-··-·---··----·-·---- ••••• -••••••••••••••••••••• -••••••••••••••••••••• --•••••• -•••••••••••.••••• -.... 0011 1. 22,21'i~I·-21,····-····-··-·················1···,··2··,1-1·····················12·--··-··· •. -••••••••• -•..••. -•• -•••. -•••..••••. -.-.--- 0011 Du ------·-·-·-·····-·····-····-····----···3····-··-······· ··-········-·····-··-·····-·-··2·· 4····-··-·······-········· ••••••• --..• --.• --- 0011

AM-····-···-·-·-··1······························,··'·1··· ··················,,·····-32·····2 ...... -...... • -.-.. -... -...... -.-.- 0'00 C. ·····_···-·-···-·-····',·-··--····-1,·-······-·,····-··· ··········1-·····--···-·-···-····· ·1·22113············1····· ••••••••••••••••••• 0100 B.n ·-·-···-··1····-·-··········-·····-·····1··············· •••••••••••••••••••••••••• -.- ••••• ·····--·,···-···',12·"··· •••••• -••••••••••• - 0'00 la ·······-···-···········,-···-·-·---··2·······-·········· ...... -..... -.--.. -..... -.-.. , .. ·,···-····1·1·1···122'···· ••••••••••••• -••• -- 0100 Sq ••••••• - ••• -•••••••••••• , ••• ,-., ••••••••••••• - •••••••••• ···········'··2··1,·-·······-·-··· ······,····1,'2·······-··· .-...... 0100 Cp .- •• --.-.---.-.-- .. --...... , ...... ,·· ...... ··-1· .. ·····2···· .. •• ·-· .... 1· .. ···1' .. ·-2·2322 ...... ------.-- 0100 Type 2 Tr .-.-.-.- •• --•••••••••••••••••••••• -•••••••••••••••• -•••• ··········--····-,-·'·-·-·1······· ·-·1'-······-·········-2·· .-...... 0'00 Ab -···1······-··············2·-··························· ···········-······1······1-11221·· ·1······1·············-,·· .-•••••••••••••••• - DIO' Av •••••••• , ••••••••••••••••••• -••••••••••••••••••••••••••• ·····],··········]···1······4·4]]2 ••••••••••••••••••••••••••• -...... DIOl C. ••••••••••••••.••.• , ..•..•....•..• -••••.••••••••••..•••• ······,········2········'···212·2· """"""""""'·1,·· ••••••••••••• - •••• - DIOl Cd ...... ----...... ] ...... ·33343432·444D2434444444231.. ··2· .. • .. •...... • .. ·'--14] .. -- ... -...... --... DIO' Et .-.- ••••••• -•••••••••.••.•• -•••. -.- ••••••••••••••••••••• 1233242··2··1·1,]2"']""']"21]· 2·················,···-··· ••••••.•. -•••••••• - 0101 Sh ...•.•••••••••••••. -....•••..••...... ••••.•.••.••.... ]··D···························,· ....•..•.•....•••••••••••• •• .•...... 0101 Gb .... ··1 ...... • ...... , ·Z·] .. " .. • .. •• ...... •• .. • .. ·2········ .... ••• .... 22.. •• .. 42'·23222'2'2 .. '···'·· .... 22···'····· .. --.... 011 Ao ········]··-·········5·································· •••...•...... •...... •••••••••• ] .•...... " ...... - '0 F. • ••.• -••••• -••••.. -•..••...••.•.••••.•••••••••••••••••••••••••••••••••••• -•••. --..••••••••.••••••••••••.• -••• , •••••• ·······1"'1211121· Il Re ••••••••••••••••••••••••• -••••••••••••••••••••••••••••••••••••••••••••• -••••• -.- ••••••• -•••••••••••.••••••••• -••••• ········-·······-32 " Te .- ••••••• -.--- ••••• -••••• _•• -.•.•. -.•••••• -•••••••.•••••••••••••••• -•••• -••••••• -.- •••••••• -•••••••••.•••••••••••••• ·········2·12·11,·· Il Type 1 v. --···· .... --.. --.. '22.. • .. ----· .... •••••• .. • .. •• .... • .. • • .. • .. 2222·· .. • .. • ...... , ...... , ...... 2213233333222----2· Il 00000000000000000000000000000000000000000000000000000000000000000000000000000000000000 000000000000000000000000 ",,',',1,,11111111 0000000000000000000000000000000000000000000000000000 0000000000000000011 0000000000000000000000''''','',,,,,,,,,,,,,,,,,,,,,,,,,, 000000000000000000000000"",""",""""""""""" """"""""""""",,,""""",,""""," 00000000000""" 000000000'11'",11111100"""""1,1,'1111,,,' 111111", 00000000000000000000000001111111000000000000000111111,,,, 001"''''110011''

species: Am - Acacia mel/Nera Ab - Acacia brevfsplca Gb - Grewia blcolor An • Acacianllot/ca Ca - Comm/phora africsna Av - ACBlphyavolkensii Ao • Acokantheraoppositifolia Ec - Euphom/a cande/abrum Ban- Bosc/a angustifo/ia Ga - Grewia similis Fa - Ficus sycomorus At - Acacia tortilis La - Lannae stuhlmannii Cd - Croton dictygsmous Re - Ricinus communis Aa • Albizia anthe/mit/ca Bq - Stercuria quenqulobis Et - Euphorbla tirucal/i Te - Trlchllia emet/ca Ba • Balanites aegyptica Cp - Commlphora pelleifolia Sh - Strychnos hennlngsii Va - Vangueria apicu/ata Du - Dombeya umbraculifo/ia Tr - Turree robusta types (1-3) can be identified, with type 2 having two subgroups. The three main • vegetation types are deseribed and related to their habitats or locations as dcpicted by the quadrat cJusters (1-111).

(1) Vangueria apicu/ata-Ficus sycomorus-Trichilia emetica type. Dther species present inc1ude Ricinus communis and Acokanthera oppo.-.itifo/i&l. The tluee dominant species ail require relatively high soil moisture. Vangueriu ,'piclI/;Wl is usually 1-3 metres in height and often Decurs in dense clumps. Ficus trees tend to he taU (8-25 metres) and frequently have diameters at breast hcight of 300-600 cm.

This type of vegetation is found in riverine habitats in the area (Group 1) (Figure 4.5). AlI but one of the nineteen sites included in this cluster group arc located along the main river or one of the smaller streams and this sample (Q83) is located close to the main river.

(2) Croton dictygamous-Euphorbia tirucal/i-Grewia bicoJortype (Figure 4.6). Thesc sites generally contain trees and/or shrubs and have higher species richness than found in Vegetation Type 3. This bush or sometimes thicket vegetation is usually found in higher elevation sites (Group II) and the samples of this type tend to have a higher species density. There are two subgroups of species that tend to occur together. Olle group (2a) consists of Euphorbia tiruca/li occurring as emergent trees with a dense understorey of Croton dictygamous. Other undergrowth speeies include GrewÙl similis, Acalypha vo/kcnsii, Acacia brevispica and sometimes Strychnos hcnningsii or Grewia bicolor. Tree species found include Sterculia quenqu/obia, with Acacia tortilis and Euphorbia cande/abrum occurring in sorne of the )ower elevation samp)es. • 69 Figure 4.5 Riverine vegetatIon in the Batemi area. This photograph de piets the main • type of vegetation found along the rivers and streams .

Figure 4.6 Type 2 vegetation, which is found mostly in hill areas. This particular • photograph is of dense Euphorbia tiruea/li-Croton dictygamous vegetation found along the base of the escarpment on the north side of the valley.

• This grouping of vegetation is found mainly in the Kirijau hills and along the lower slopes of the escarpments along the north of the valley. The shruhs and hush are • rarely more than 1-3 metres taU with trees generally 8 to 10 metres in height. The second subgroup (2b) consists more of Grewi.1 bic%r-ColllmiphoTél

africana-Lannea stuhlmannii Grewia bieolor in conj unction with COnJm;pJwTél

africana or Sterculia quenqu/obia dominate the vegetation of the Kitoyo hills, in the

southeast corner of the study area. This vegetation is not generally as dense as that

of type 2a.

(3) Acacia torti/is-Balanitesaegyptica-Euphorbia candelabrumvegetation type (Figure 4.7). The dominant species is Acacia tortilis, which grows to 8-12 meters on average.

Figure 4.7 Acacia tortiiis-BaJanites aegyptica.Euphorb/:1 candeJabrum type vegetation, with an undergrowth of an Aloc sp. (Iugaka). • .. )

• 71 Other species that occur occasionally are Albizia anthelmintica, Commiphora

africana, Acacia mellifera and Sterculia quenqulobia. The underlayer is quite sparse

• type in most places, although c1umps of dense vegetation do oceur sporadically. This is scattered throughout the study area, generally on the valley floor or in transition zones from plain to hill areas.

There is a cluster of samples that contain Acacia nilotica as opposed ta Euphorbia candelabrum or Balanites aegyptica. This was not separated out as a

distinct type because the samples for the two possible subgroupings are geographically interspersed.

4.3.2.3 Ordination The distribution of quadrats are depicted along the first and second axes of ordination (Figure 4.8). The groups defined from the TWINSP AN analysis are indicated. Most of the samples are located to the left of the diagram, with nineteen sites occurring ta the right-side. Those quadrats belonging to samples group Il are found more towards the right-side of the diagram and group III quadrats are located in the upper, central position of the diagram. Group l or the river sites are located ta the right-side of the diagram. There are a few outliers or samples whose location in the ordination space do not correspond with the TWINSP AN clusters. Quadrats 33, 50 and 137 (Type 3) fall within the lower left-hand side of the ordination diagram. The first axis in the se ordinations is probably associated with a soil moisture gradient. Those sites on the left represent areas of drier soil moisture while those on the right are moister (river sites). Also, the quadrats occurring to tbe left of the diagram are generally areas of higher elevation, which affects soil moisture content.

• 72 Figure U Detrended correspondence analysis (DCA) ordination lliustating specleS space. The TWINSPAN cl uste rs of quad rats are dep 1 cted. An envi ronlen tal in terpretat Ion of the fi rs t DCA • ms 1S offered.

1

1 1 1 Group 111

1

1

1 1 s >015 1 < >014 1 1 1 1 02 __...... 1 076,0126<18 o PON JI(LM B ~~~ 06 < W R 034 < 1 Group II a<

dry loist

Legend:

Group 1 t • 08. 017, 055. 081 $ • 079; !"o 0125; @ - 051, Q73; '·09, 044

Group II 33= II 1 a: 96,31,33; c= 135; d= 139; e= 138; g: 130; h: 132; i: 136; j: 22 ; k:I24; A= 91; B: 85; C: 102; D: 4; E = 3; F = 1; G: 5 8 = 46, 58, 95; 1: 90; J: 94: J( = 92: L = 20: K = 32; N= 100; 0 = 127; p: 105; Q: 101 104; R = 88; S: 68 ; T : 53; U: 59; V: 89; ,,= 15; 1 = 35 Group III f :13.40,54,61,117; 1 = 48, 107; 1: 99, 118; n: 43; 0: 24, 42, 69, 109 p: 140 q = 112; r = 36, 235, 110, 115; s = 66 ; t= 47 Q: 60; v: Ill; v : 106, 108; 1 : 41; l': 38 ; z : 33 • y: 29, 84, 86; Z: 74, 119 Species distributions are indicated in Figure 4.9. The classification of species • obtained by the TWINSP AN analysis are obvious here. The species classed as vegetation type 1 are located together to the right side of the diagram. Those species diagnostic of the plain samples are found towards the upper part of the second axis. Dombeya umbracuJjfera, which is included as part of the first TWINSPAN species

cluster is shown to he an outlier in the ordination diagram. It only occurs once in a

plain quadrat but twice in a hill quadrat.

4.3.3 Irri"ation Channels

The riverine vegetation in the Batemi area tends to he quite different in

species composition and density, as discussed above. A total of 22 species were

found along the four irrigation channels inventoried (Table 4.7). Of these 22 species, the most abundant tree species are Cordia africana, Ficus sycomorus, Trichilia emetica, Ficus sur, Capparis sp. (mrera) and Vernonia amygdalina, with 47, 47, 27, 11, 14 and 14 individu ais respectively. Cordia africana and Ficus sycomorus each

account for about 25 percent of the trees found in the irrigation channels. The most represented family in the irrigation channels is Euphorbiaceae, with

three genera and four species. Capparaceae is represented by two genera and three

species and Moraceae by one genus and three species. In terms of number of individual trees, Moraceae has the highest abundance with 13 trees. Boraginaceae, as represented by Cordia africana, is second with 47 and there are 21 individuals of the Meliaceae Family.

Most of the tree species are 15-25 meters in height and Many of them have

diameter measurements of 300-600 cm at breast height Most of the trees are quite

• 14 Figure 4.9 Detrended correspondence analysis (DCA) ordination displaying samplcs space. The vegetation types identified in TWINSP AN analysis are indicatcd. Vegetation types identified in TWINSP AN are indicated. The riverine vegetation • species are located to the right of the diagram. For full species names see Table 4.6.

+ +

• Table 4.7 Inventory of Irrigation Channels.

Genus and Sp. Vernacular DigoDig Mugh. Tot Rel. • 1 2 1 2 Den. Anacard Jaccae Lannea sp. mtoregani 1 1 .50 Astcraceac Vcmonia amygda/ina mtcmbcrcghu 2 1 8 3 14 7.04 Boraginaccac OJrdia africana mringaringa 16 15 12 4 47 23.62 Capparaccae Capparis sp. mrera 14 1 IS 7.54 Capparis tomcntosa mhoroboboi 1 1 2 1.01 Euphorbiaccae Bridc/ia micrantha bara 4 1 S 2.51 Ricinus rommunis mbono 2 2 4 2.01 Guttiferae Garcinia livingstonci mbigo 4 4 2.01 Mcliaœac Trichilia cmcûCJI mdaghamira 19 3 1 4 27 13.57 Moraœac Ficus nataknsis mgumu 7 2 9 4.52 Ficus sur mtoyo 1 3 13 17 8.54 Ficus syromorus mkoyo 19 16 8 4 47 23.62 Rubiaœac Vangucria apiculata mgholoma 4 2 1 7 3.52 92 38 46 21 199 Capparaceac Macrua calophylla nasoloko P Cacsalpiniaceae Senna didymobotrya senetoi P Euphorbaceae Acalypha frutirosa msanoni P Acalypha JXlniculata mnywamayi p Fabaœae Cassia bialpulam mbenyenye P Malvaceae Hibiscus calyphyllus kiraraha P P P Rutaceac Clauscnia anisala mnyoka P Sapinadaceac AllophyHus abussinicus P Vcrbanaceae ClcrodcndruIfl rotundifoüum kijut·a P • old. There are also a number of shrubs found along the channel!>; two of the major

ones being Clerodendrum rotundifolium and HilJ1:"'cus cn/J'phyl/us. Typical irrigatIon • channel vegetation is illustrated in FIgure 4.10. Thirteen species found along the irrigation channels were encollntercd

nowhere else in the valley (Table 4.8). Many of thesc arc specles that arc typically found in moister environments. The spccies richness a}ong the irrigation channcls is high relative to the richness of the surrounding plain vegetation.

Figure 4.10 Typical irrigation channel vegetation. This photograph iIIustratcs il section of one of the irrigation channels in DigoDigo . •

• 77 Table 4.8 Species found only along Irrigation Channels . Species Vernacular • Acalypha fruticosa msanoni Acalypha parJicu/ata mnywamayi AllophyJ/us abyssinicus Bridelia micrantha hara Capparis tomentosa mhoroboboi Cassia bicapu/arsis mbenyenye C/ausenia anisata mnyoka Ficus natalensis mgumu Ficus sur matoyo Hibiscus calyphy//us kiraraha Maerua calophyJ/a msoloko Trichilia roka mtembereghu Vernonia amygdalina

4.3.3 Other species There were also fifteen species that did not fall within either random sample sites or the irrigation channels (Table 4.9). Sorne of the species, such as Jatropha curcus were found within village areas. Others, such as Warburgia salutaris were seen during the ethnobotanical surveys and did not fall within the confines of the defined study area (Figure 4.1). Many of the species (for example, Pappea capensis, Rhus quantiniana) are found within the plains but are not common and thus were not encountered in a quadrat.

4.3.5 Landeover Map

The resultant the matie map depiets four landcover classes (Figure 4.11). These classes are: 1) bushland and woodland thicket, 2) woodland 3) wooded grassland, and 4) grassland with scattered trees, which incIudes agrieultural areas and • 78 Table 4.9 Species encountered but not eounted in any of the methods . • Family Species Vernaeular Anaeardaceae Lannea schimperi mginkinywa Rhus natalensis mbwensha/msigiyo Rhus quantiniana msymbeuhcmhc Burseraceae Commiphora marke; kidingho ka mgongo Cane llace ae Warb'Jrgia salutaris mscga Combretaceae Com"retum sp. msaghu Euphorbiaceae Cro:on megalocarpus ekitilambu la tropha curcus mgulungulu Liliaceae Aloe sp. elongo Mimosaceae Acacia sp. mzironi Acacia nubica oldebe Moraceae Ficus populifolia mgagatya Papilionaceae Ormocarpum kirkii mlemenj agu Sapindaceae Pappea capensis kiboboyo Tiliaceae Grewia sp. msabasabwa

villages. The classes are described below. The bushland and woodland thicket c1ass consists of vegetation cover of either

woodland or bushland type but with the woody plants in sueh close density that this

type is often impenetrable. When vegetation forms locally impenetrable patehes il

is termed thicket (White 1983; Lind and Morrison 1974). Bushland can he defined as areas with more than 40 percent bush cover. Bushes are woody plants intermediate between a shrub and a tree, that is, usually between three and seven

meters tall (White 1983). The appearance of the bushland and thicket varies, as does

the aetual plant shape, aceording to the rainfall it receives (Lind and Morrison 1974). The wood land contains trees of up to 18 m in height, with an open or

cantinuous but not thickly interJaced canopy (Pratt et al. 1966). Woodland is similar

ta bushland but with a taller and more c10sed canopy (White 1983). • 79 • • •

Figure 4.11 Landcover map for the Bateml area. i_ • 1 I~. rIT ---,-~ ·-r--r-r . .. &: -:--.-.;;; ..., 1 _ IN: ~

Scale 1:75,000 I­ -..J WVIlet Smith )<)

Grassland is usually defined as consisting of less than 10 percent woody cover

(White) or 2%(Pratt et al. 1966). This class also contain village and agricultura 1 areas. Figure 4.12 depicts the study area, with the random samplc sites (groupcd into three vegetation types) overlayed on the supcrvised classification. This ovcrJay

reveals that there is fairly good correlation between vegetation site types élIul the

landcover density classes. Most of the Acacia torti/i.., vegetation type t'ails within the

wooded grassland or grassland classes while most of the EupllOrbùl tiruea/II-Crotol1 dictygamous sites are shown ta faU within the thickct or wood land arcas. Type 1 vegetation is found near river sites as already discusscd.

The locations of the villages are also depicted in Figure 4.11. This iHustra tes

that ail of the villages do not have the same access to the various vegetation types.

The sub-villages of Eyasi, Mgero and Mgundu do not have easy acccss to bushland

and woodland thicket, which is the source of much of the firewood used by villagcrs. AIl of the villages have reasonable access ta wood land and wooded grassJand cover, where there is still a reasonable abundance of species for fuelwood and timbcr.

• 81 • • •

Figure 4.12 Masked Landcovcr map showing the distrihution of the random quadrats in terms of the three vegetation types. -,

J J 5KM 1

Scale 1:75.000 Wynet ~mlth1993 Legend: • - Type 1 Bc.!:)hland and w('ndland thlCket - Wooded Grassland --- - ElevatIon - Type 2 - IrngatIOn Channeb • - Type .3 tk>i-Woodldnd '--, - Grassland and scattered trees --- - Rlver~and ~tream~ 4.4 Conclusions • The Batemi area consists of three main vegetation types that are associated with three different types of habitat. The di~tribution of the various vegetation types

and individuaJ spccies is essentiaJ for identifying and monitoring species vulnerability.

These data providc a oaseline inventory that can be used with the species use data

tn identify species that may require attention in conservation or resource planning. The landcover map may assist in this process. The next chapter examines the process of assigning use values and assesses the abundance of key socioeconomic or valued species.

• 83 Chapter S. Identifying Conservation Priorities

• 5.1 Introduction In marginal or semi-arid areas, such as the Batemi valicy, wherc vital rcsourccs

are under increasing demand, sustainable use and conservation of rcsourccs Will

require identification and study of valued ecosystem componcllts or kcy socioeconomic species. From the Batemi per1lpectivc, this approach will asslst in

protecting the integrity of the resource hase for thcir continued usc. Tins is one 01

the goals of KIPOC in deslgning a sustainable resourcc plan. On a mano-lcvcl, the

regional and national governments require such mformation 10 cnsnre cquity in lalld­

use and resource management planning and to undcrstand use pressures on the

environment. The international conservation movement recoglllzes the necd for peopie-oriented conservation information hccause of failllres of past efforts.

In arder to identify conservation priorities, it is first neccssary to asscss locally

important resources. If no attempt is made to sornehow index relative values, the

default is that ail uses and ail species are treated as equal. Treating ail spccics as

equal will not address local pressures nn me environ ment and local vulnerabilities to

environmental change, nor will it help ta identify more endangered spccies. Value

indices can he used in relation to availability or abundance information to idcntily

possible conservation priorities. If ail species were of equal use value, it would he

expected that common species will he used more while rare ones are uscd less.

Deviations from this pattern may reveal significant situations where species that arc

highly valued and intensively used are ecologically rare and perhaps vulnerable, or

where species that are abundant are ignored or underuscd, perhaps retlccting

untapped resources . • 84 This chapter records qualitative local information on species value and conservation pricTities but it also attempts ta use field dBta ta generate qualitative • indices that could he uscful in conservation work. It is exploratory and is intended to show how factors could be used rather th an ta show definnively what priorities

should he. Nonetheless, the exploration is discussed in light of field knawledge of the conservation situation and sorne recommendations are made.

5.2 Salient Issues While sorne conservation priorities are established by the international scientific community, locally important species and ecosystem companents can be identified only through a local perspective. Various studies have shawn that local

knowledge and traditional management practices are important sourœ~ of information for conservation programs (see AIcorn and Oldfield 1991a; Boom 1987;

Johannes and Halter 1986). Most studies of plant use, however, merely record use

without attempting to assign vaJ~.;:,. Frequently, species of value are named but there is littIe information on methods of determining the value and there is no quantitative

basis for comparative assessment This offers titde on which ta establish priorities. Little work has been done on assigning non-economic values ta components

of the biophysical environment.6 Where markets exist for commodities, it is often

6 Valuation of natural resources is a field receiving much attention (see Brown 1990; McNeeley 1988). Most theories attempt to assign economic "alues to t'ses. This is not the interest or intent of the type of use-value being discussed here. Rather, the goal is a non­ economic index of the relative importance ofvarious species in an attempt ln identify species that may require more attention because of greater demande • 85 assumed that the market works ta establish values for thosc colllmoditics 7. Supply should balance with demand through competitive lJltlding fOi scarce cOI.llllodltics that

• mort' drive prices up and thereby encourage produccrs to produl'e and protect

sources of supply. But assuming thls mechanism Will prote ct ccologlcal reSOllll't.'S that

do not have significant market value can lead (and has Icd) to ceological catastrophe.

Sorne 0~her strategy has ta be developed ta recognizc the rcal valuc that ccological resources may have in non-market economies.

Factors influencing utility value of a commodity or servlcc are 1) the

importance of the need that is being met and 2) the range of options for mectmg that need. The value would be directly proportional to the importance of the need heing

met and inversely proportional to the range of alternatives for mcetmg that need.

Tht:~, ifvalue is V, 1 is importance of the need and S the numbcr of suhstitutes, then

V is a function of IlS. The vulnerability of a rencwable resourcc is rc\atcd 10 the rate

of production or availability (A) relative to the rate of consumptlOn (C). Thus,

vulnerability or endangerment (E) is a function of CfA. Establishlllg conservation

priorities based on local cultural needs wou Id involve relating the value (V) to the

degree of endangerment (E). Important species with high vulnerability woukl he

priorities; low value species with low vulnerability would not he. Thus conscrvation

priority (P) is a function of E x V or CfA x IlS.

Is this conceptu3lization useful? lt may he in an abstract way for formalizing

ideas about conservation priorities, but it may also help to highlight practical conœrn~

or note significant change where sufficient data exist. Quantifying these paramctcrs,

7 Note that this does not deal with the "deep-ecology" issue of inherent or intnnslc value of species independent of their utility value. ft attempts only to address the stcp bcyond market valuation, where commodities do have utility valuc but, for various reasons, do not have appropriate market values. • 86 however, is difficult, perhaps impossible, in practice partly because importance is a

subjective assc~~mcnt that will vary culturaily and, probably, between individuals. • Availabliity and number of substitutes will change with economic, technological and environmental circumstances. Nonetheless, the difficulty of determining precise

values should not precJude atterdpts ta examine the issues.

Practical examp!t's of evaluations, such as those that assign values to key

sociocconomic spccie:" are in an carly stage of development. One possibility is ta

assume a rclationship between number of times a species is cited and its importance

for that use. Johns et al. (1990), although not attempting to assign a use value, do

limit their reporting of indigenous plant use ta species that are cited a minimum

number of times.

Another possibility is ta assign use values. Pranee et al. (1987) outline a

method which assigns a major use value of 1.0 or a minor use-value of 0.5 to each

use (If a species. The criteria for assigning a major or minor use-value is based on

respondent information and authors' observations but the exact method of duing this

is not well-explained. This IS a coarse scale of evaluation. The method of totalling

ail use values highlights those species that are multi-purpose but undervalues ~hose

which may he highly-valued for one specific use. The authors, however, do recognize

the j, .1portance of species that can not he substituted and the need ta pursue

identification and conservation of these species. Despite obvious flaws, Pinendo­

Vasquez et a/. (1989) have used this system in an attempt ta quantify, on a

comparative level, resouree use patterns.

Another method involves the assigning of a hierarchy of usefulness by the

villagers or respondents themselves (Joint Forest Management 1992a, 1992b). In this

technique, the interviewers have respondents indicate the value of a species for a • 87 given use, l'lffering numbers of seeds or other small ohjects are lIsed to demonstratl'

~he rda;iVf import<~nu: of speclt:s. Although more '1l11e-COnsul1l1ng than the

• '1 .: ,'\' appr~" .. -ring vi'lue ~ased on responses, t111S system offers good potential as

the \; :h't'" Ir' ctiy in.1icated by the local re~pondents.

The me!!"" expkJt<:d in this study arc number of cItations, a scaling of use

vafuesy. as we3! as a 1actor for intensity of use. The intcntion IS to sec how thc

incl~lsion uf ea~h <,f ,' .. ',e factNs intlul~nces the analysis.

5.3 Met" >1' ,'~'f

5.3.1 r{. at;Îç,,,;~;,1a ',' \J,.!,.! -_ ,i 1 pr~ctices

Data" ,,' :~I~al "" ,. ".:dge and conservation practices wcre collectcd dming

informaI interviews Wl~H (he village groups (discussed in Chapter 3) and with village

leaders in August 1992. The information l'rom these interviews 15 qualitative in

nature and is discussed as such. Particdar types of data collected include local

conservation practices, knowledge about woody vegetation distribution and local vicws

on declining species.

5.3.2 Assigning Quantitative Values

The use data from Chapter 3 provides the basic information upon which to

explore methods for assigning value. Food and medicine arc not inc1udcd in thesc

calculations as the method of collecting data was different.

i) Citations

A count was made of the number of times a given species was mentioned for

a given use in one of the group interviews. The first analysis was simply to rccord • 88 the number of c1Qsses of use for which a species was cited regardless of the number • of citations. The second analysis weights the ref,ults according to the number of citations for each use.

iJ) Use valUes The second approach was to assign an importance value to the need that a

species is fulfilling as dcme by Prance et al. (1987). To overcome sorne of the limits

of this method, the approach taken here is to consider how important an use is and

how many alternatives there are for achieving or meeting the same need. This can be done by giving each species a weighting proportion al to its use in meeting that

need.

Rather than using two values as Prance et al. (1987) did, a need value was

assigned to each use category or sub-use category, ranging from 0 ta 100 percent

(Ta hie 5.1) rather than treating aIl uses as equally important. For example, in

construction, 60 was assigned to house pales, 20 ta fences, five ta furniture and two

ta hyaena traps. Species are not ail considered ta he equally important for a given

use and sa are assigned a weighting proportional ta the number of citations for that

use. The numher of citations per species per use was taken ta he proportional ta the

importance of that species that use. If there are six species cited as contributing ta

a specifie need and one accounts for 75% of the citations for that use, it is assurned

that it is of greater importance th an one that accounts for 10%. For each species, the use importance value, such as 60 for pales, is multiplied by its citation proportion

numher. This effectively addresses the Ils component in the model proposed above.

The resulting number is termed the use-species value for that given use. This

procedure is carried out for each sub-category and then aggregated to obtain an

• 89 overall category use-value for each species. This procedure is thcn applicd to l'ach • general \;ategory of use ta obtain a fina: overall use valllc tor cach SpCClCS. One potential problem with this approach is that Il only \I1chl\lcs woody species. High values may be assigned ta woody spccies ha:icd on low slIbstitlltahiWy

white there may be herbaceous or succulent species that arc cmploycd for thc usc.

This is certainly the case for rape.

~.3.3 Method for Investigating Endangerment and Conservation Priorittcs In arder to explore the endangcrment or vulnerability of SpCCICS, it is neccssary

to examine consumption levels relative ta production or ahunJa.lct'. As no

quantitative information on amounts of consumption was collcctcd tluring the field

work, consumption values are estimated on an ordinal scale hetwcen onc and four,

with one indicating low use and four a high volume use. For cxamplc, within

comtruction uses, pales require higher amounts of wood and thus arc assigncd a

three, while furniture or rape is given a one. On the gcncrallcvel of use, fircw()od accounts for the highest volume of woody vegetation use and th us reccives a four,

white implement use will he quite low and thus reccivc a one (Ta hie 5.1). Thesc

consumption values (C) are then multiplied by the use values (V) already calculated

for the construc;.ion categories and for the aggregate use value. This is donc as

conservation priorities are likely ta include those species that are highly valued and are consumed at a high rate relative ta their abundancc. The conservation status of various species !s investigatcd by plotting each of

the different types of "values" (citation, V, V*C) for construction UllC, as weil as for

the overall V*C values, against the abundance data presentcd in Chapter 4.

Medicinal citation data (from Johns et al. n.d.b) are plotted against den ~ity as weil .

• 90 Table 5.1 Nurnbcr!. used to calculate values for the various types of use . Construction and Implement uses subdivided into their respective categories.

U~C # citations Importance Consumption • 1--- Con!.truction Poles 53 60 3 Bee 39 10 1 Gate 3 2 1 Trap 5 2 1 Door 5 5 1 Rope 3 5 1 Furniture 2 5 1 Fences 10 20 3 Implements w. stick 13 5 1 rungata 1 1 1 d. stick 4 1 1 handle 2 2 1 Bow& A 7 2 1 Tootn 5 1 1 Other 2 1 1 Firewood 32 75 4 Services "1 15 1 1 i

5.4 Results and Discussion

5.4.1 Traditional conservation practices

The Batemi practice certain forms of conservation; theyare weIl aware erthe

importance of trees to their environment and have rules governing use of certain

areas. The Batemi have distinct management strategies for woody vegetation. This

applies mostly to the well-forested irrigation channels that are found within the areas

around the four main villages and the subvillage of Eyasi. The irrigation channels are

extremely important to the Batemi as explained in Chapter 2. In Ïtlterviews with

various villagers, the conservation of trees along the watercourses was consistently • 91 discussed. Villagers conflrmf'r1 t}le traditlOllal practicc of kavmg the !Iees along the • watercours~s as these were comadered Important for pn.'scrvlllg w,ller now and thll~ ensuring continued :rngatlon. Cuttmg nt lices .1long the ~tr;:al1l~ or the millll IIVl'r

is a110wed but is proh;hlted along the IrngatHlIl channeb. ThIs .. tnrt control ha~ hecn

a traditional Batemi law for many gcnclatlons and severe t\lle~ aIl' kVled ag

transgressors nf the prohIbition. Only the tradltlOlHlI Wenamue r1a~~, who have

heredltary entitlemcnt to the channels, have the f1ght to eut trc('~ 01 glve perll1l~SIOn

for others ta do sa.

These sanctions dernonstrate a de facto conservation program that may rcikct

recognition of priority spccies Of the hydrologlcal irnr,ortancc of protectlvc vegetation

along irrigation channels. If there are nQ! sdnctiol1s again~t lise l'Iscwherc, It may

reflect a tradition in which the intensity of the Impact of human use was not

significant relative to the availability of ecological reSOllrccs.

As dlscussed in Chapter 3, the Batemi utihze a large range ot woody species

found in the fields and hiIls surrounding thclr villages. The 102 SpCCIC~ uscd by the

Batemi (Chapter 3) represent a large portion of the total number 01" species

encountered in the area. Sorne of the species that were rnelltIOncd were Ilot

encountered Juring the survey work (Table 5.2). Of the JOI specics actually

inventoried during the biological survey, 84 (83%) were rncntioned as fulfillmg sorne

function.

The Batemi possess an intimatc knowledge of the habitat:.. of variolls spccies

and this can be helpful, especially in the cases of rare or les~-widelv dl~tnbllted

species. Most villagers were able to describe the general location or habItat type for

the les~ common specles or for specics not found in their irnmediate area (Tahle 5.2).

For instance, Baterni villagers at the west end of the valley were able to dc~cnhe the

• 92 Tahle 5.2 Srcclc~ indlcatcd as uscd hy the Batemi but which were not encountered dunng ~amphng. The locations are tho~c givcn by vlllagers, or in a few cases • ob~crvcd f1r~t hand hy Johns (1992). SpcCJ(~~ Vernac~t1a[ LocatIOn

[Jo ..,C/éI conacca Jugumetu Sale plain Ou J.~sa cduiI.~ lumemc Bush (seen near Mdltu) Clcrodcmlrllm myncOJdes mgutugutu woodland in mtn. COI1J/11/phora madagacacensls mSlslyo Soutn of bwelo J)J(.;hro.... tachay.~ cinaca kiholi hillside Ellphorbm cUlIcaléJ mrumye hillslde Ficus glumosaJ mbugl llarn.\onw ahyûnmca toro high p Ip.v.(Mditu) Myrsll1c arncana ngashe Lolio!.1do Plumh.lgo zelanica lughiri Typha ~p. kiroya (Oldonyosambu) kljerwe far in Bwelo lorieni mountam areas

location of a species such as Salvadora per5ica which is only found in the Kisangiro

area. Othcr spccles (e.g. Croton megalocarpus, Mimusops kummel and Ormocarpum

kirkiI) were de~cribed as bemg 'lTIountain" or 'bush" species whieh were not easily

accessible. Somc areas in the valley are named after species that oecur in dense

numbers. For example, there is an area ta the east of the Kirijau hilIs that is known

as makurehendane élfter the ... ernacular ekurehe or makurehe (plural) tree

(Ormocarpum sp.) that uscd to be found there.

In a few villages, Ioeals dis~ussed the problem of disappearing species.

Mugholo and Samunge villagers named Acacia mellifera and Cardia africana as two

species that were hccoming Icss common. The first species, as already discussed, is

a highly-valllcd, multi-pllrposc sp.:cies whiIe the second is highly-valued as a beehive

matcrial. In Oldonyosambu, Cordia gharaf and Ozoroa mucranata were the two

main species regardcd as bcing noticeably more difficult to find. Each of these • 93 species are multi-purpose, hcing used for at lea~t twn gcncral purpo~es . • The Batemi dlsplHy an m-dcpth knowkdgc of thel! CnVIrlHll1lCnt. Any MHIlh.1 conservation strategy for the arca must recognize thelr me of l-c~ourccs, ,ml! would

benefit grel1tly by incorporatll1g thelr knowledgc and re~()urcc lise plactu:cs.

5.4.2 Use-values

The range of values for thc ditlerent methods (citatIon, V and V*C) for the

construction category, and for the overall value wlth COnSlll11ptloll (V*C) arc glven

in Table 5.3. Figures 5.1 to 5.6 IIldlcate the relatlOl1shlp hetween the ... c values and

abundance. Tnese diagrams isolate species that may warrant speCIal conservation

attentbn

5.4.2.1 Citations

Figure 5.1 illustrates the nurnher ot I.!~e categories of cadI ~pecles agalf1~t

abundance. The figure shows that there are rnany i11ulti-purpmc specle~ that do not

appear to be aIl that abundant in the arCH. ACë:lcia md/liera, although one of the

most prized specics only has a density of 10 indivlduals per hectare. Many of the

rnulti-purpose species have low densities of under 20 indlvlduals pcr hectare. Only

Croton dictygamous, and then Acacia tortil/s, Acan;, 111 !of/Cil, and GrcwJa fnco!or

have relati"ely high densities in .c1ation tn the number of cltathHlS.

Based on the second method of totallmg ail cltatIOn\, the 11l0~t valllcd or key

local species for construction pmposes IS Acacm mc/Mera, wlllch ha~ tcn cltatl()n~.

The otherfrequently mentioned ~pecics are: Mimu.wp.,> kllmmel, Cordm nlnc(Jn(J, and

Ficus sycomorus, aIl with seven citations. Whcn exammmg thc~c numhers in rdatlon

to abundance (FIgure 5.2), there arc obvious differenccs III thc abllndance of ~pccje~

• 94 • -

Table 5.3 List of values for various construction species based on the two methods of assigning value. The columns of values are: building citation number, builing (V), building (V*C), implement (V*C), fire (V·C), service (V·C) and an aggregate value (V*C).

Abbr. Genus and lp8Ci" Vemacular B.Cit. B.Value Build-V·C Impl Flre Serv Total Abp NJrus precatorius mnyete 05 05 Ab /leac/a brevispica mhereki 9 9 AI Acacia senegaJ mhuti 1 1 13 34 34 Ag /leacia goetzi msigisigi 2 1.4 365 9 12.65 ~m Acacia mel/ifera mng'orora 10 10.3 27.8 0769 28 56569 ~ Jlcacia nilotica kijemi 6 57 143 18 32.3

~t Acacia torti/is mkamahe 5 5.3 13.9 37 50.9 ~ Jlcacia xenthoph/oee mrera 18 18 lAc·v Jlcelypha vo/kensii munyuri 028 028 ~ Albizia anthe/mitica mrira 1 03 026 026 ~1 Aloesp. a/ambola 9 9 ~ Aloesp. kihandi 9 9 Ba BtJlfU/ites aegyptica mjuÎya 1 2 6 9 15 Blln Boscia angustifolia munyagu 2 1.4 3.65 214 5.79 Bm Bridelia micrantha bara 3 1.6 39 3.9 ~ Capparis sp. mrera 1 04 0.4 9 9.4 p.a C/ausenia anisata mnyoka 0.5 05 b.r C/erodendrum rotundifo/ium kijuba 0.5 0.5 FP Combretum padoides mkong'ongi 1 1.5 1 5 1.5 ~m COf'TIbretum molle mtewamgongo 1 1.13 34 9 12.4 Ptt.a CommiphortJ africana kidlrlgheta 2 4 12 12 Pt CommiphortJ ellembekii mwaraheta 6 2.41 4.68 468 py..p Commiphora pellifolia muluba 6 42 104 10.4 Pat Cordia africana mringaringa 7 27 4.93 4.93 Pet.a CorditJsp. mgombeha 3 34 10.18 9 19.18 Pt.m CorditJsp. mto 0.77 9 9.77 Pet.g Cordla gharel muhabu8u 1 1.13 3.4 3.4 • •

Abbr. Genus and species Vemacular BCit. B.Value Build-V*C Impl. Fire Serv. Total Cd Croton dictygamous mgllalugi 1 1.13 34 0.92 9 1332 Cr.m Croton megtJIacarpus ekitalambu 1 1.13 3.4 3.4 De Dichrostachays cinerea kiholi 4 5.4 16.2 162 Du Dombeya umbraculifolia gwaretu 2 23 6.79 0.57 736 Er Euclea racemosa mraganetu 3 077 0.77 0.29 1.06 Ec Euphorbia cande/abrum kiroha 9 9 Et Euphorbia tirucal/i kidlgho 18 214 2014 Fa Ficus sycomorus mkoyo 7 2.4 2.37 9 11.37

~b Grewia bic%r ebuaheni 4 4.5 1358 4.2 17.78

~1 Grewia trichocarpa esere 0.77 9 977 Hf Haplocoe/um fo/ioosum egirigirya 6 68 204 18 313.4 He Hibiscus ctJIyphy/fus kiraraha 0.1 0.1

~c Jatropha curcus mlemanjagu 02 428 448 L Lanneasp. mtoregani 2 051 0.51 , 051 M Maerua sp. kasingiso 428 428 Mk Mimusops kummel ghanana 7 5.3 14.35 214 1649 lem Ozoroa mUCTanata mgalat, 6 42 1096 1096 Pc Pappea capensis kiboyoyo 9 9 Rc Ricmus communis mbono 0.67 067

~p SaJvadora persica msago 1 1

~q Sterculia quenqulobia mugurumetu :3 4.5 673 673 2099 ~h Strychnos henningsii klbunla 3 3.4 1019 '8 9 Irs Tec/ea s/mphfolia mwararJ 1 036 026 026 Ire T"chll/tJ emet/ca mdaghamlra 9 9 Uv UvtJfltJ schleffen mSlhmbu 1 1 7 167 1 67

~a VanguentJ apIeu/ata mgholoma 1 2 6 6

~am VernonitJ tJfT'Iygdttlma mtembereghu 1 15 15 1 5 1885 ~c Zanthoxylum chalybeum mulongo 3 34 965 02 9 les esughubetu 1 036 026 026 kJ klJerwe 2 23 679 679 Ik ,,- 0.51 __ -- ktteo 2 0.51 051 Figure 5.1 Multi-purpose \ alues plotted against availability .

4i~------~--~----- M M M ------~~------• c Cd.s Sh Am An Cd

3 Mk. )( )(. . .. )(.. '" ...... )( . )( ...... Ced Er L Ag Fs Gb At .~ Cr.m Ze

of ~ 2 ...... 'o~ "ë~~~' '~Cd: x· ··~~:~······E:OV;·············· ...... ls Cm.mk Caf As Aacm.a Cd.s

O+-~~~~~~~--~,-~rM~~--r-~~~~r---~~~~~ Q 1 10 100 1000 Species density (#/hectare)

Figure 5.2 Construction citations plotted against abundance. 1 Am

._ u • .-...... • .. .. n...... •••• ...... •• u ...... ou .. ..

.. *" Caf...... Fs *" ......

*" ...... * .. * ...... )11< ...... )11< ...... Om Hf Ce Cm.p An ...... * ...... Al ...... *" ...... * ...... Oc Cd.s Sq Gb ...•.... ~ ...... *3\E-' Sb ...... Er*" Ze .... "'''}N: .~m,a ...... Ag,L Ban Du Ts,Uv ...... *". * ..... *M.Cfl'· ..* .... * ...... )11< ...... * .... , ...... C.Cp.Cd.g Aa Ba Va Cd

1 10 100 1000 • Speeles denslty (#/hectare) that have the sante ciution number. For example, Ficus ,"ycomorus has a denslty ot • 8.7/hectare as opposed to Cardia afric/lna, which has a dcnsity of O.7/hectilfl' or Mimusaps kummel which was not seen during the sampling. The latter two specil's

may therefore require more attention than Ficus sycomoru. .,. Other species tltat may

be considered as warranting special attention are Ozoroa mucr.mat'l, Haplo('ocJu11l

folioosum and Dichrostachays cinerea.

5.4.2.2 Value

The use-values (V) for the various categories are given in Tablc 5.3. Figure

5.3 illustrates the construction values in relation to abundance. Thcr~ is a scattcring

of species in the diagram. Species that have high values but low densitlcs arc ACllCÙl

mellifera, Haplocoelum folioosum, Mimusops kummel and Dichrostllchays ôncrcél.

Other species that may warrant attention include Ozoroa mucTémata, Cordùl élfm:;uw and possibly Cordia sp. (mgombeha) and ZanthoxyluIn chalybcum. Thcrc arc also

species, inc1uding Croton dictygamous, Acacia tortilis, Grewia bicolor and V'J1Jgucrùl

apiculata, that are quite abundant but have relatively low value. Thesc spccics would

therefore he low on the list of species requiring attention.

5.4.2.3 Endan~erment and Priorities When a volume-of-use coefficient is added to the equation (V·C), the

resultant values are slightly different (Figure 5.4). The most highly valued and used

species are basically the same as in Figure 5.3, with Acacia meJ/ilèm having the

highest value, followed by Haplocoelum folioosum. Dichrostachays cincrell is slightly

higher than Acacia l1i1otica using this approach. A few other spccies also change

positions relative to each other, including Sterculia quenqulobia - Strychnos henning,c;jj

• 98 • Figure12i 5.3 Construction use-values versus availability (IlS =V) . 11) . *Am

~ ~ ::1 8 ii!I > c: 0 :cl * Hf 6 ~", ·T 5 (,) Dc* *Al 1'd ~ CI 4 ~ jiCm.p *Gb .. eCI CI

Figure 5.4 Construction use-value with consumption factor included (V*C) ~~------~

*Am 25

Hf .).tii......

...... ArI ...... '" ...... Oc'"* ** * Al Om *Cm.a Gb Cd.s * ...•..... ~h* Crri:p' Zc Sq Du Caf * * * Va 5 ~ .. J\ri" )IlCf: * 68··· ~ Bm ~d.g ** As * Ban *Fs Cd* V~, '*' Aa o '1' 1 o 10 100 1000 • Specles denslty (#/hectare) and Commiphora africana - CommipilOra peJ/eiféJlia .

The overall aggregate values for specics (hased on four categories of use) arc

• r listed in Table 5.3 and thcir relationship to availahility is l11ust atcd in Figure 5.5.

The species indicated as valuable are gcnerally consistent wlth the previous figun:s.

Acacia mellifera, Acacia tortilis, Acacia nilmica and HélplocOc/ll/11 {OIIOO.'HW1 arc ail

species that have high values. They do not, howcver, have the saille ahumlancc III

the area and therefore there are sorne species that may require more attcntion. For

instance, Acacia mellifera, which has a higher use value than Acacia lortilis (56.6 vs.

50.9), has a rnuch lower density (lO/ha vs n.7/ha). Hap/ocoelum fo!too.mm and

Acacia nilotica have the sarne relative relationship, with the formcr having a 11Ighcr

use value (38.4 vs 32.3) but a much lower density (2.7/ha vs 34.7/ha).

AlI of the figures iIIustrate a range of values per dcnsity and no lincar

relation~hip to abundance. This marked deviation from a linear relationship hetwccn

use and abundance suggests differences in the way the specics should he vicwed from

a conservation standpoint. Do the often cited sp -,cies that arc rare rcqUlre special

attention? Is their rareness due to rates of exploitation? Is ahundancc stablc? What

would be the social consequences of local extinction'!

Analysis of the density of"key" species reveals a numbcr of interesting factors.

These inc1ude low densities for a number of species, with sornc not even found in the

immediate vi~ inity of the villages, such as Mimusops kummel. Other spccies, such

as HaplocoeJum foHoosum, Dichrostachays cinerea and Mimusops kummel havc

relativeiy high use-values but lower densities. Many spccies that have high

construction use-values, such as Haplocoelum folioosum and DichrostacJwy.<; cincrCél

have quite low species density. Certain species, such as Acacia tortilis and Acacia

nilotica are shown to possess high use values and relatively high dcnsities. Still others,

• 100 Figure 5.5 Aggregate use-value plotted against availability . oo~------______-,

X • Am xAl

40 Ô• )( ~ Hf Q) ::J 30 ~Q) en ::J E ~ h 20 Cd.s xS ..... ;C X~······ .. Dc>< Zc >01: )( ~Al )( Cd.a)( Ce ~s)( Ec )(Va ~ >< Ban Q O~olf~~ïïTT~~~~~~~~~n+~~A~a~~~A~c'~V",r-__~-r~~~ 0. 10 100 1000 Specles denslty (#/hectare)

Figure 5.6 Availability of medicinal plants.

Ha

)( ...... Sp

...... •...... •...... ••. ')C ••••.•...•....•...... •.. Aa Xsh xOm x As x X ...... CI,m ...... ' .. "...... )( ...... Cd...... x Er Ar?" xAx Ba x At.

10 100 1000 • Specles denslty (#/hectare) such as Salvadora persica and Eue/ea racenwsa have bath lnw densities and low usc­ • values and th us presumably lower priorities. Overall, the most highly valucd spccics is Acacia mel1ifera, which the loeals consider a strong, rcsistant wood. As this sperics

does not have a high abundanee, it may he a suitahle spceics to single out for special attention. The identification of this species as potentiaHy vulncf'lhlhty rctlccts the information provided by the local residents (see Section 5.4.1) in tcrms of specics that

are most highly valued and declining. There are a few further notes of interest regarding specics availability and use. The restricted use of species such as Euphorbia tirucalli is usually rclated to their

distribution. Euphorbia tirucalli is abundant along the escarpment and in thc Klr~all

hills and this is reflected in its use in Digodigo and Mugholo where it provides easy access to abundant fuelwood. This species is also a common live fencc in these two

villages.

vnly four of the species found only along the irrigation channcls arc lIscd hy

the Baterni and the se are ail fairly minor uses. Ficus sur is used only for food;

C/ausenia anisata is used for toothbrushes. Vernonia amygdalina is uscd ior huilding

and medicine. Bridelia micrantha is the only species that has a highcr use valuc duc

to its use for construction. The low usage of these species -- 30.7% of spccies as compared to 83% species usage overall -- rnay he a reflection of the restrictions on cutting along irrigation channels. The distribution and abundance of a numher of the medicinal specics provides

sorne interesting insight into their use (Figure 5.6). Most of the specics used for

rnedicinal purposes are either extrernely rare or are not found in the area altogcther.

For example, sorne of the most widely used medicinal species, Harriwmia abyssinica

and Warburgia saJutaris are not found near the villages. Myrsine africana i.. only • 102 found in Loliondo, about 30 kilometres away. Harrisonia abyssinica is found to the • west of the study area, near the Samunge subvillage of Mditu (Johns 1992) while Warburgla saJutaris is found in the hills, about an one and a half hour walk behind

Mugholo. Commiphora madagascar is found to the south of the study area, near

Ghamasa Hill, about ten kilometres from DigoDigo and Mugholo.

5.4.3 Assessment of Methods

A number of difficulties became apparent during the exploring of methods to

assign use-values. For example, the division of the need-importance coefficient by

the number of suhstitutes greatly affects the importance of each use-species importance value. This is problematic in many ways. Within the construc1ion

catt~gory, for example, the range of species cited for house pales may reflect the

importance of the need, while furniture, with a much lower need-importance, involves

only a few !lpecies. The range of species used for poles reduces the overall

importance value for that column below that for furniture, a less important need.

The differences hetween using the number of citations versus the generated

values can easily he seen by examining the placement of species in Figure 5.1 versus

Figure 5.3. Th,. positions of sorne species, such as Acacia me/lifera or Croton

dictygamous, do not change greatly between methods, while others species are

affected quite dramatically. Ficus sycomorus and Cordia africana which appear quite

high in terms of the citation numbers have much lower positions based on the calculated use-values (V). Haplocoelum folioosum, however, is placed relatively higher in Figure 5.3 as opposed to Figure 5.1. The relative positions of Ozoroa

mucranata and Dichrostachays cinerea also change, with the former being more

"valued" in the citation system and the latter being more important in terms of the

• 103 calculated value. In this respect, the use of a calculated value secms worthwlllle, as • highly valued species such as Ficus sycomorus and Cordia africi/Tli.l are actually not used much at present, either due to restrictions on their habitat or low availahihty.

The difference created by adding a volume coefficient is evident in the relativc

position of a number of species. Higher use volumes add to the value or intcnsity of

use of a species and therefore increases its overall use-value. The resultant

difference is obvious in comparing the change in the posItion of Ficus sycomorus,

whieh as 3 very valuable, but not high volume use SpcCICS, has a lowcr vulnerabihty

when volume is taken into account. Certain species, such as Strychnos henningsii,

inerease in vulnerability with the addition of the volume of use coefficient, as docs

ZanthoxyJum chalybeum to a slight degree.

Overall, the differences between the vaïious methods seem adequate to justify further exploration of the possibilities of sueh approaches for attempting to identify

possible conservation priorities. Refinements should mclude work on the meélns of

assigning relative use values and levels of consumption coefficients. Possibilities for

solving the present problem of subjectivity would he to colleet more quantitative lise

values and to quantify the local consumption of dlfferent species and different

categories of use. Attention to variations in local use pattern<: in relation to spccics distribution would serve to identify species that may requiTe more attention in a

loealized area.

s.s Olnclusion

The management and conservation of these species must he addresscd within

the socioeeonomie and ecological context of the area. Baseline data as colleeted in this researeh can assist local communities and governments in planning for sustainable

• 104 use and conservation of these resources. Local knowledge and traditional • conservation practices such as the conservation areas in the Batemi area, provide basclinc structures that can be built upon in resource and conservation planning.

Ignoring these Jocal practices and values would only jeopardize any plans that would

he implemented. Further investigation of local ecological knowledge about species habitats, ecological preferences and speeies interactions would bolster this process. The results of the different methods for assigning use value, as explored in this chapter, suggest that further work and refinernent on the means of assigning values

would he worthwhiJe. Methods of having loeals assign quantitative values, actual

quantified consumption levels, and ,'ariations in use patterns are ail factors that would

bolster these types of approaches to identifying conservation priorities. Based on the methods as foHowed in this chapter, species such as Acacia mellifera, Haplocoelum foIioosum and Strychnos henningsii rnay he species that require further study and attention.

• 105 Chapter 6. Conclusions

• In view of the interreIationship betwt:en the natural environment and its sustainable development, and thl: cultural, slh:ial, ccullomic and physical weIl being of mdigenous people ... efforts to impie ment . , . sustainable development ~hould rccogniœ, accon,!11odate, pwmotc and strengthen the raie of indigenous people and their cOl11l1lunities. United "Nations, Agenda 21: Section 26.1

Addressing the goals of j\:~enda 21 will require great advances in our ability

to translate ecological requisites and cultural aspirations into pr.\ctical management

strategies. The great challenge of protecting bioùiversity must be faced by

recognizing the range of culture systems and resource use practices that co~exi<;t wlth

the world's biodiverslty. This thesis has attempted to explore one \Vay ot promotmg

and strengthening the raIe of the Batemi in protecting their irreplaceable resource

base. The three specifie goals were to:

1) investigate local use of vegetation

2) study the abundance and distributIon of woody vegetation in the arCH

3) experiment with assigning use~vallles to species and with using these values to

identify conSf'rva tion prioritie~.

As discussed in Chapter 2, there are a number of pressures in the an~a,

including a grawing population and changing social and polltlcal !->tructures that altect

land use and resource management. The conversion of land into cultivated fields and

gardens is taking place primarily on the plains, so the resources l'rom this community

may come un der increased stress as population growth continues to IIlcrease the

demand for agriculture. Firewood reserves are largely on hllbides, so as the demand

for firewood grows the problem of hillside erosion muy increase. Therc is cvidence, • 106 such as wldesprcad gully erosion and locahzed areas of bush yc1earing, that these

pressures may have an IncrcasIngly adverse effect on the area. It 1S • thercfore Important that a resourcc and conservation plan be deslgned and Implcmented. A local group, KIPOC, and the District Council are In the process of

workmg towards thls goal, a goal that must incorporate local needs and practices.

Chapler 3 ha~ shown that the Bateml make use of a large percentage of the

"natural Il vegetation found in thcir environ ment. They use over one hundred woody

species found In the ~urroundmg areas, which constitutes 83 percent of the spccies

cncountcrcd during the random samplIng. The Batemi have defimtc preferences for

vanous specles, depending "n the speclfic use. For example, valued construction

specles Include Acacia mellifera, Hap!ocoe!umjo!io().\um and COI-dia afrrcana, while

valued ImpIement ~pecles Il1clude GrewLa bu:o!or and Strychnos hel1n/llg.\/1.

Chapter 4 pre~ented data on the hiOloglcal arca that the Bateml lIlhabit. The

ar~l contams a large flul11bcr of woody .,pccies (over 100), most of which are used

by the Batemi for at least one purpose. The natural vegetatiOn can be divlded into

three C01lll1lUmtles that are found wlthm hillslde, plain and nverine habitats. In

addition, there are the IrngatlOn channels, which can be considered as more diverse,

dense examples of the nverine vegetation, which seems to be due to their special

conservatIOn status as well as hlgher moisture avatlability.

This range of habitat types allows access to a broad arr

The placement of the villages with respect to the spatial distribution of vegetation

types shows that each village, with sorne exceptions, has reasonable access to each

coml11l1ntty. The irrigation vegetation is accessible to ail villages in the valley. It

is val lied for Its ecological role in preservation of the Irrigation system and hence

cutting is restricted and the use of the woody species is practically ni!. Similar

• 107 vegetation is found in Type 1 or riverine vCfctation, wlllch IS found scatt~n:d

throughout the valley. Type 2 vegetation is the major source for fuel and

• bUilding umbcrs and it contams many valued, scarcer specH.'s, sllch a'l A('(/('/(/

mellifl'rù and Wùrburg/a sll/llIaris. Because il IS rcstncted malllly to tllld,ets on 11111

sites, lt IS not equalIy accessible ta alI the villages. The ~ub-villages of Eya'il, Mgero

and Mgundu, have less access ta the bush and wood land tllidet. Type 1 vegetatlll/l,

which occurs mostly in "woodland" or "woodcd grassland" fOllllatiolls, 1" wldl'ly

accessible. Species found in Type 3 are also used for fuclwood and constllll"tloll,

although these areas do not seem to be as he..1.vily exploited as Type 2 for these

purposes.

There is enough spati.lI variation 111 the plant colllmllnily that variations III

resource u~e practices were scen to vary from village 10 village. Villagers Icndcd to

cite a higher reliancc on plants that were close, ~lIch a<; the hlgh me of l:'ul'horb/{/

tirucalli for fuel and live fcnces In DigoDlgo and Mugholo. The exception tu thls

is the practice II1VOlvlIlg medicinal ~pecie~, where sorne of the Illo,>l valued oncs, such

as Warburgia sa lU/ans and Harmonia abysSlnlCa, are par!lClIlally rare and only

available at great distances. People will travel long distances 111 ~carch of thc~e

varieties.

In Chapter 5, Batemi conservation knowlcdge and traulllOnal pracllccs were

discussed and shown to be relevant to dcsigning and implcmcnting a cOI1'\ervallOJ1

3trategy or sustainallle resource plan. Thcir knowlcdge of the cconOllllC properlic~

of available resources, their traditional conscrvmg strategy for local Irrigation

channels and their knowlcdge of spccies habitat') would have bcncfÏl~ If IIlcorporated

into any regional or natIOnal plan. Thcir dependencc on the re~()urce"i ~lIgge~t~ a

strong interest in maintaimng thc viabllity of the eco~ystcm and thclr hl':>torlcal record

• 108 of interaction with the ecosystem suggest that they do have ways -- implicit or

explicit -- of ensuring coexistence with a large range of naturally occurring species.

• Chapter 5 also explored methods for ineorporating local values and practices into a quantitative index of resource valuation. The assigning of use-values to

various species illustrates the difficulties involved in establishing objectlve or at least

consistent conservation priorities. By showing the range of species that are valued

for specifie uses, the work did highlight the importance of effective conservation.

By comhining biological data on the abundance and distribution of the various woody

species with use data, key socioeconomic species that may represent conservation

priorities have been identified. Certain species, induding Acacia mellifera and

Haplocoe/umfolioosum were identified as being of potential concern, or priorities for

further work. The quantitative values presented in Chapter 5 are debatable of course,

but they do serve as a way of integrating information and they do appear to be

effcctive in identlfying specles that should at least receive doser scrutiny as

conservation strategies are developed.

The data used in this study were gathered al a single time, but repeated studies

at later times or at other places could help show change over time or differences

between places. These too could be important signaIs for :onservatlOn planners. It

is hoped that the data that has been presented in this thesis can be of assistance in the

Batemi area, in terms of providing baseline data, illustration of spatial extent of use

of habitats, and in identification of species of potential interest or concern. Further

work on identification of key ecological species would also beneficial.

It is clear that the goals set by Agenda 21 and by many international

conservation agencies will only be achieved if present approaches to resource

management and development are radically modified. Among the many changes that

• 109 are required is a recognition of the ecological system of indigenous populations. The • Batemi have an extensive knowledge of the land they occupy, use a large array of the native species and have resource-use practices that have alloweu them to co-exist

sustainably with their environment for generations. As thcir population grows and

economic relationships change, they will undollbtedly alter thcir rdationship to the

land. Successful conservation will require their being able 10 Illcet thcir aspitations

without undermining their resource base.

Clearly related to this issue is the requirement of e~tablishing conservation

priorities in settings where market forces cannot be a~sumed to he adcquate to

identify valued assets and regulate their management. The life sustaining natural

resources of the Batemi have a utilitaiian worth that exists entirely outside of markets

or cash economies. Yet the value of building materials is c\early as great here as il

is anywhere.

Given the pressures of "econornic rationalization" that are reshapillg many

developing countries, it is vital that sorne method be establishcd for iùentifying and

codit)ring valued resources. Where conservation priorities are bcing determineu at

least in part by the needs ot the local population, the encodeJ values will he\p

establish conservation priorities. This thesis has experimcnted with variolls ways of

Iinking local use data with estimates of consllmption and measures of ahundance to

raise questions about conservation priorities. The convergence between the reslilts

of this approach and the priorities cited in interviews with local people, suggests the

methods are worth purslIing. It is hoped, therefore, that this thesis can provide

insight into reorienting approaches to conservation and development.

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• 119 Appendix 1 : Materials used in land-use analysis . • Material Details Source Aerial February 1958, 1:40,000 Fairy Air Survey, held at photographs 35TN8, 62 and 63 and Mapping Office m Dar es 35TNlO, 146 and 147 Salaam, Tanzania Aerial January 1972 - 2-35 LI9-S Geosurvey, held at Mapping photographs Office in Dar es Salaam, Tanzania Landsat TM March 1, 1990, Scene 61 Photograph of print hc1d at print the Serengeti Research Institute, Serengeti National Park Landsat TM March 1, 1991, Scene Data frorn Serengeti Research digital data 169-061, Path 16. II stitute, Serengeti National Park Topographie 1:50000, Sheets 27/1 Mappmg OftIU:, Dar es maps (1968 and 1979) and 27/2 Salaam, Tanzanta (1978 and 1991)

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